[Computer Applications in the Earth Sciences] Geothermics in Basin Analysis || High-Resolution Temperature Logs in a Petroleum Setting: Examples and Applications

HIGH-RESOLUTION TEMPERATURE LOGS IN A PETROLEUM SETTING: EXAMPLES AND APPLICATIONS

ABSTRACT

David D. Blackwelll and Graeme R. Beardsmorel

Richard K. Nishimori2, and Richard J. McMullen, Jr.2

IDepartment of Geological Sciences Southern Methodist University, Dallas, Texas

2Mobil Technology Company, Dallas, Texas

Examples of high-resolution temperature logs measured in oil and gas fields in the United States are presented and the pertinent features useful in basin analysis are discussed. We point out that wells suitable for equilibrium or near equilibrium temperature logs usually are available, and we describe by examples criteria for the evaluation of the quality of a highresolution temperature log. Examples of temperature gradient logs from two fields in the Paleozoic-age Anadarko Basin in Oklahoma, one field in the Cenozoic Gulf Coast Basin, and one field in the Mesozoic/Cenozoic Sacramento Basin in northern California are described and their application to the analysis of basin thermal structure discussed. The major criteria that can be used to evaluate the quality of the log are level of (temperature) noise, presence/absence of negative/zero gradient sections, degree of correlation with other geophysical logs, and well to well comparisons. Even logs that are not in complete equilibrium contain significant information compared to a typical set ofBHT points. The development of memory PIT tools and their deployment in the field for production logging indicates that the potential now exists for routine collection of high-resolution temperature data in hydrocarbon settings worldwide. Because the thermal regime of many boreholes in producing fields may be closer to equilibrium than has been thought in the past, the new temperature capability can be used in a practical way. High-resolution logs can furnish detailed information on the gradient, the ratios of the thermal conductivity values in hard-to-sample lithologies to those iIi lithologies easier to characterize, and ultimately more precise understanding of the thermal regime (whether conductive, convective, etc.) in individual wells and sedimentary basins. So the use of these types of high-resolution logs can be added to the petroleum explorationist's data sets to be used in basin thermal analysis as an important new source of information that can be used to increase the precision or estimate the errors of the models developed based on conventional BHT's and cuttings measurements.

A. Förster et al. (eds.), Geothermics in Basin Analysis© Kluwer Academic/Plenum Publishers 1999

2 BLACKWELL, BEARDSMORE, NISHIMORI, AND McMULLEN

INTRODUCTION

The generation of petroleum products from organic material is driven primarily by temperature (e.g. Connan, 1974). Modeling thermal conditions in a sedimentary basin through time therefore is a critical step in assessing the maturity of petroleum source beds, the timing of petroleum generation, likely fluid migration paths, and reservoir locations. A crucial constraint on past thermal conditions is the present-day temperature distribution within the basin. An accurate determination of present-day thermal regime thus is a vital step in assessing a hydrocarbon prospect.

Heat transport within a sedimentary setting may be by conduction (direct heat transfer between adjacent grains) or advection (heat carried by moving fluid). In a thermally equilibrated, purely conductive setting, where heat transfer by fluid movement within or between sedimentary layers is negligible, vertical heat flow generally can be assumed to be constant with depth and, together with thermal conductivity, will define the temperature distribution. Therefore, present-day vertical heat flow is a vital parameter in assessing organic maturity in prospective petroleum locations.

Theoretically, heat flow is a relatively simple value to calculate because one need only measure the thermal gradient and thermal conductivity within the conducting strata and the conductive heat flow is determined fully because Q = - KxdT/dz, where K is thermal conductivity, dT/dz is the vertical thermal gradient, and Q is heat flow. Because both gradient and thermal conductivity have equal importance to the final heat flow and in calculating basin thermal regimes as a function of time, accurate thermal history determination requires accurate measurements of both parameters. Historically, however, accurate measurements of these two parameters have been difficult to obtain using typical exploration data sets. To this day, there is controversy about the accuracy and precision of the typical techniques used in the petroleum setting to measure both subsurface gradients and the in situ thermal conductivity of earth materials.

In situ thermal conductivity, inherently, is a difficult quantity to determine. It can not be measured directly, but has to be deduced from indirect thermal measurements of covarying properties obtained from well logs or core and (more usual) cuttings samples. Coupled with a limited understanding of the relationship between conductivity values measured in the laboratory and in situ, it is inevitable that the uncertainty in many heat-flow measurements might be expected to be associated primarily with the thermal conductivity component because there are no such intrinsic difficulties in measuring thermal gradient. Relatively inexpensive and simple technology allows temperature measurement to a precision of 0.001 °C, so thermal gradients can be calculated to a ±0.5°CIkm precision at I-meter resolution. Such precision effectively reduces uncertainty in the thermal gradient component of heat flow to I to 5% in most instances. However, the dominant source of temperature data used in thermal analysis of sedimentary basins is well-log header Bottom Hole Temperatures (BHT). With these BHT data, thermal gradients, even on km scales, rarely can be determined to better than ±5-15% (see Jessop, 1990 and the recent error discussion by Lee, Deming, and Chen, 1996), and thus there is not sufficient resolution to discriminate significant lateral and vertical thermal conductivity variations from heat-flow variations. Combined errors imply that the heat-flow values determined using BHT and cuttings measurements have typical errors of at least ±20%. Jessop (1990) has described one of the few comparison studies using a tightly constrained and comparable sets of the two types of data. In his study multiple BHT points from wells in an area 3Ox30 km2 surrounding sites of four wells with detailed temperature logs were compared. He concluded that the average of the BHT was within 10°C of the actual temperature but

HIGH-RESOLUTION TEMPERATURE LOGS 3

showed that the BHT data had no vertical resolution of gradient because of the depth clustering and scatter of the BHT points. He emphasize that because of the completely different information content, both types of data are essential for understanding the thermal state of sedimentary basins.

Given the ease of acquiring quality temperature data and the great advantages in application compared to BHT data, with the added bonus that in situ thermal conductivity ratios also can be obtained in most situations, it is difficult to understand why they are so rarely sought. Use of such data should reduce heat-flow errors to on the order of 5-10% and thus result in at least a 100% decrease in the error of present-day heat-flow measurement. Some of the reasons include the lack of readily available commercial in-the-field temperature logging equipment, the unsuitability of open-hole temperature logs made immediately. following completion of a well, and a belief that equilibrium temperature logs can not be made in typical petroleum well settings. The objective of this paper is to discuss all of these arguments in the light of modern technological advances in equipment and in the understanding of the thermal regime of wells. As part of this discussion the equipment, methodology, processing, and interpretation of downhole precision temperature logs will be reviewed.

Many thermal problems in sedimentary basins have remained unsolved because of the poor resolving power ofBHT data and the limited number of detailed equilibrium temperature logs described in the petroleum exploration literature. For example, the only book dedicated to using temperature in hydrocarbon exporation (Gretener, 1981) can only point to one example temperature log from a well in sediments that illustrates the inverse relationship of thermal conductivity to thermal gradient (Gretener's fig. 4.3-3 and fig. 4.6-4, and copies of paper field log prints). In the heat-flow literature there are numerous examples of the behavior of detailed temperature logs in sediments, but these typically are not available or known in the basin analysis field. Thus questions such as the thermal effects of salt, refraction of basement uplifts, direct detection of hydrocarbons (Forster, Merriam, and Davis, 1998; McGee, Meyer, and Pringle, 1989; etc.), and the effect of fluid flow on the temperature field in sedimentary basins (Deming and others, 1992; Majorowitz and others, 1998; Bodner and Sharp, 1988; etc.) remain open to experimental study. However, because of recent changes in technology the methods are at hand to make temperature logs in sedimentary basins everywhere on a routine basis as was not possible in the past (e.g. Wisian and others, 1998). These recent tool developments are part of the motivation for this discussion focused on the use of detailed, accurate temperature logs.

The application and interpretation of high-precision thermal gradient logs is best illustrated using real examples. For this purpose, a number of examples are described from several different sedimentary basin settings show how precision temperature and gradient data enhance our knowledge of the thermal regime in a well. It is important to understand how thermal gradient logs relate to lithology and other well logs, how the geologist can be confident that a temperature or gradient log represents equilibrium conditions, how we can ultimately use a gradient log to make a best estimate of heat flow in a well, and how we can extrapolate our knowledge to other nearby wells.

Several other examples of precision temperature logs and their correlation to lithology and other log information were presented by Blackwell and Steele (1989a, 1989b). There are other examples in the literature as well, although on a more limited basis (Demongodin and others, 1991, for example). Other examples specific to Kansas (Blackwell and Steele, 1989b), Nebraska (Gosnold, 1990), and the Anadarko Basin were described by Carter and others (1998). Gallardo and Blackwell (1999) illustrated how the addition of a few accurate, detailed temperature logs may be used to calibrate in situ thermal conductivity values in a sedimentary


basin. They showed that in a conductive setting those calibrations, together with lithological analyses, allow predictions of basin temperatures as accurately as, but independent ofBHT analyses. Thus the possibility of real error analysis of the conventional BHT -cuttings techniques (e.g. Lee, Deming, and Chen, 1996) may be possible. Brigaud, Chapman, and LeDouaran (1990) and Griffiths and others (1992) have described detailed systems for calculating thermal conductivity from well logs, but they did not have any detailed in situ thermal conductivity distributions to compare with the results of their predictions. Thus the combination of the two data sets should allow a level understanding of present-day basin thermal structure not heretofore obtained.

The focus in these cited papers was not on the thermal regime in individual wells vis a vis evaluation of equilibrium conditions so the details of the well settings were not discussed except that Carter and others (1998) do have brief discussions of individual well thermal conditions. The particular objective of this paper is to illustrate how, in real hydrocarbon settings, useful temperature data can be obtained, some ofthe characteristics of how thermal data quality may be recognized, and how high-quality thermal data may be utilized in basin thermal studies. In addition the examples we present here extend and further illustrate the relation between thermal gradient and rock type. A location map of the wells referred to in this paper and those described in detail by Blackwell and Steele (l989a, 1989b), Gosnold (1990), and Carter and others (1998) is shown in Figure 1. The location of the Anadarko Basin, referred to in two of the examples is shown also. Detailed temperature-depth logs have been described for the different setting of sedimentation in an active tectonic region, coastal California, that is for the Ventura Basin (De Rito and others, 1989) and the Santa Maria Basin (Williams and others, 1994).

CANADA

MEXICO

Figure 1. Location map of wells with high-resolution temperature logs: fields with wells described in this paper (crosses); locations from Blackwell and Steele (1989a, squares); locations from Blackwell and Steele (1989b, dots) ; locations from Gosnold (1991, stars), and locations from Carter and others (1998, pluses).


APPARATUS

Temperature can be measured only by direct methods. That is, to measure the temperature of the Earth we must physically lower instruments down available holes. The temperature at points away from the holes must be interpolated from known data. Highprecision instruments for measuring downhole temperature have been available for many years. Most are electronic in nature, utilizing thermistor or platinum resistance sensors as tl).e temperature sensitive component (Gretener, 1981; Blackwell and Spafford, 1987, for example). Once calibrated, a simple resistance measurement is sufficient to determine temperature. Platinum resistance thermometers are superior to thermistors in that they are accurate and stable and have a nearly linear resistance-temperature response for a large temperature range. Unfortunately, their resistance is small (25-50Q), so if analog wireline techniques (measurements of voltage or current using a multiconductor electrical cable for connection to the probe) are used heavy, low resistance cable is required to maintain accuracy.

The simple analog downhole tool contains a thermistor or platinum sensor in a probe that descends the hole. Electrical contact is maintained with the surface and real-time thermistor resistance is monitored using a digital multimeter. Such. systems are simple to design and operate, but are limited by a need for four leads and high cablehead leakage resistance. Temperature resolution of 0.001 °C precision is possible with careful design (Blackwell and Spafford, 1987).

Commercial temperature logging tools typically convert resistance to frequency downhole so that a single wire (with steel sheath) is sufficient for logging and cable head leakage resistance can be lower with good results. A problem with these tools is that the frequency cOtinting typically has been for too short a time interval to give the O.OOI°C resolution needed for high-quality logs and 0.1 °C usually is the accepted resolution. Modem electronics now allow a 0.001 °C temperature resolution with frequency tools if so designed.

A classical production tool is the Kuster or Amarada bomb mechanical pressure/temperature tool run on a slick-line (a solid wire used for mechanical strength only). At the present time downhole-computer slick-line pressure/temperature (PIT) tools are replacing this production tool technology (Larimore, Goiggon, and Bayhn, 1997). Real-time surface monitoring of downhole pressure and temperature is not possible with these computer tools because they are self-contained with onboard battery, memory, and processing chips. The electronics may be housed in a sealed Dewar flask for operation at high temperatures. Computer tools generally use a platinum temperature sensor for greater temperature stability. Recording is initialized at the surface and the tool and the surface computer are time synchronized, then the tool is simply lowered down the hole and the depth recorded as a function of time by the computer connected to a digital depth encoder at the surface. Probe resistance is recorded automatically at preset time intervals, and when the tool is returned to the surface, data are downloaded onto a PC where the temperature ( and pressure) are correlated by time with depth to generate a conventional property-depth log. Computer tools are more expensive than wire-line tools, but are more versatile. Slick-line is less expensive than wireline, and can be pressure isolated more easily for logging high-pressure or flowing wells. Also, computer tools generally are designed to withstand high temperature and pressure, so are more suited to logging in deep, hot, pressurized, producing or other hostile environment wells.

The temperature sensor should be mounted as near to the leading tip of the probe as possible, so as to minimize disturbance to the well fluids prior to temperature measurement. The probe should be a rugged construction of brass (or similar high thermal conductivity material) and sealed to keep borehole fluids away from electrical connections. One operational


problem is that a cage usually is used to protect the sensor tube during logging. During openhole logging the cage typically gets plugged with mud and drill cuttings effectively increasing the time constant of the tool from seconds to minutes and seriously degrading log qUality.

An accurate depth log must accompany any temperature log. To this end, some sort of odometer must be included with the logging system to record accurately the length ofline that has been fed from the winch. For some deep or hot wells, corrections may have to be applied to compensate for elastic extension and thennal expansion within the wire. With wireline equipment depth can be recorded simultaneously with real-time temperature data and stored on a PC or other memory device. Computer tools include an internal clock and record data as time-temperature(-pressure-etc.) pairs. A time-depth log must be collected independently at the surface so that subsequent processing can merge the two data sets to produce the desired depth-temperature pairs. These tools are capable of collection of research quality temperature logs if the tools are calibrated (Wisian and others, 1998). The range of equipment now available from service companies (Larimore, Goiggon, and Bayhn, 1997) makes it possible to collect precision temperature gradient data under any conditions and in any locations where hydrocarbons are located.

A completely different type of temperature logging system has become available recently for well logging. It is referred to as a Distributed optical fiber Temperature Sensing system (DTS) and is based on the Raman effect of back-scattered laser light in an optical fiber. It has several major advantages over other types of logging systems. The DTS system is able to provide repeated, near instantaneous measurements of temperature along the full length of the fiber without disturbing the surrounding bore fluid. This makes it ideal for studying transient events (e.g. GroJ3wig, Hurtig, and KUhn, 1996; Sakaguchi and Matsushima, 1995). It currently is of limited precision (0.1 0c) and depth resolution (0.25-1.Om) compared to other systems (Forster and others, 1997; Wisian and others, 1998) but provides data unattainable by other methods.

METHODOLOGY AND PROCESSING

Precision temperature logging will yield only highest resolution of true formation temperature (and gradient) if survey procedures are planned carefully and followed. When planning a temperature logging survey, several factors need to be considered. Is the hole in thennal equilibrium? What temperature and depth resolution are required? Could there be convection or production disturbances within the hole and how will these degrade the quality of the log? Many of these questions cannot be answered with certainty and one of the objectives of this paper is to present examples oflogging in actual field environments that illustrate some of the effects, and lack thereof, that can degrade temperature log quality and thus develop empirical data on the conditions necessary for obtaining high-quality temperature data.

Ensuring Equilibration

Precision-temperature logging can not be conducted directly after drilling. This puts it at odds with openhole logging techniques. In order to obtain meaningful temperature results the well fluid must be in thermal equilibrium with the surrounding rock strata. For this to hold true, the fluid must be allowed time to achieve thermal equilibrium. Any event that disturbs


the well fluid column also causes a thermal disturbance. Such events include drilling, production, and logging. The amount of time required for equilibration depends on the magnitude of the disturbance and is difficult to quantify so empirical examples will be presented. Thermal equilibrium is more likely to be at least approximately approached in preor post-production logging situations where the well environment is more conducive to collection of good temperature logs in any event.

Drilling always causes a great thermal disturbance. Continuous circulation of large volumes of fluid through the well during the drilling process disturbs the equilibrium temperature of the surrounding strata by an amount from which it can take months to recover completely. The longer the drilling time, the greater the recovery time. Ideally, at least three times the drilling time has been cited as the minimum time that should be allowed to pass before logging a newly drilled well (Jaeger, 1961). However, Carter and others (1998) reported temperature logs from wells in the Anadarko Basin, some of which had been logged at a rest time approximately equal to the drilling duration with acceptable results. Of course the drilling time is shorter in the bottom of the well so the temperatures in the deeper part of a well will approach equilibrium faster in an absolute sense than the shallower part.

Production, or removal, of fluids from a well, also causes a thermal disturbance, but the magnitude is not as great as for drilling. The amount of time required to reequilibrate depends strongly on the construction and production history of the well. A typical production well is cased with 15 cm steel pipe, cemented, and produces through 5-7 cm (2-3 in) diameter steel tubing. This configuration acts similar to a heat exchanger (Ramey, 1962) and so gradients are less disturbed than temperatures. If production rates are moderate, as they may be toward the end of the life of a well, the thermal disturbance around the well will be small and not vary much with depth, and thermal gradient equilibrium should be attained in the tube, except in the immediate vicinity of the production zone(s) a relatively short time after production is halted. If flow is through a larger tube, or at high rates, the disturbance will be greater and a longer recovery time will be necessary. In general, though, logging can be carried out several weeks to months after production has ceased. The well construction of cemented casing and tubing also contributes to lower gradient noise by removing hole size variations and reducing the effective hole diameter and thus convection noise (see next).

In most fields there are wells that have been shut in for considerable lengths of time for various reasons and require no further equilibration period. To ensure completely static conditions we may install a packer above the perforations in pressured wells. If the cable is packed off at the surface during logging it is not clear that the in-hole plugs are helpful in improving the resulting log quality.

The act oflogging a hole, itself, will disturb the well fluids with the motion of the probe. Logging should be conducted ideally DOWN the hole to ensure that the temperature of undisturbed fluid is measured. Most other logging procedures run UP from the bottom of the hole. The disturbance by the probe is considerably less than that caused by drilling or production, and generally a day should be sufficient for reequilibration. Logging upwards, or immediately relogging a hole may give satisfactory results if fine detail is not required in the log. Such logs generally are noisier than first-run down logs, but medium- and broad-scale temperature trends are retained.

Optimal Logging Speed

Efficiency dictates that logging should be conducted at the maximum rate that willretum the quality of data required. Logging speed is limited by two factors; the spatial resolution


required on the log, and the thermal lag effect of the probe. Logging speed translates directly into data point separation if sensor output is recorded at specified time intervals, the usual situation for computer tools. It then is simply a matter oflogging at a rate to return data at the required depth interval. Electric line tools are designed to trigger at a regular depth intervals (e.g.O.1m). From a practical point of view recording temperatures at 0.2 to 0.1 m (3 to 6 in) is sufficient to obtain maximum thermal gradient resolution in a typical well situation.

With each finite distance the probe descends, the temperature changes by a finite amount. It takes a finite time for this temperature change to propagate through the body of the probe to the thermistor or platinum sensor. The time lag may be only on the order of seconds, but if the descent rate is rapid, this lag translates into an effective depth offset on the final temperature log and a loss of high-frequency variations. The exact value of the time lag depends on the thermal bulk, or time constant, of the probe. In general, more robust, thick or stainless steel probes have a higher thermal bulk and longer time lags than flimsy, thin or brass probes. The environment within the hole also may conspire to increase the thermal bulk ofthe probe as well. An uncased well typically will be muddy, and mud can cake in the protective cage over the tip of the probe, dramatically increasing the time lag of the instrument. Figure 2 illustrates the depth offset and loss of detail that can result from such a situation. This hole was logged prior to setting a shallow casing string by a commercial logging company and immediately thereafter by our electric line equipment. There was a lost circulation zone at 60 to 70 m that was heated by the loss of fluid. The commercial log with the plugged probe locates the zone at about 90 to 110 m because of the lag effect and broadens the apparent zone of fluid loss. There has been some study of the use of deconvolution to obtain the hole response from a temperature log made at a speed above that at which equilibrium is maintained (see Nielsen and Balling, 1984, for a discussion of the topic).

100

E

:5 200 0. a.> o

300

------------.... ":::.--..::.---- - ....... _----- .......

- l.!W Ci::·;;;;;~;;eJ --~----f ) I /' \ /' J\

1\ \

Old Maid Flat 7 -A, Oregon

8/17/80 Commercial

8/17180 SMU

~ \ l \ ,,\

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400L-L-~-L-L~--L-~~~-L~~--~~

10 20 30 40 Temperature, °C

Figure 2. Lag effect of mudcaked sensor. Example is from Old Maid Flat #7a near Mt. Hood, Oregon (Blackwell, Murphey, and Steele, 1982).


Generally, in clean, cased holes, logging speeds of 0.1-0.3mJs are optimal with probe time constants of 4 to 10 seconds, assuming that the cage does not get plugged with mud, cuttings, etc. In our logging we have preferred not to log at speeds fast enough to require deconvolution for increased depth resolution, and because of the problem of plugging of the probe at which point the time constant becomes so long that the quality of the log is severely degraded. Even a relatively fast log, in a clean hole, with a heavy commercial probe returns useful information, however. Given reasonable probe time constants and logging speeds the resolution of formation temperature and gradient is limited by the amount of thermal convection in the fluid column as described next, so that present equipment is capable of returning maximum information on formation gradients in almost all logging situations.

Processing

Little processing, other than prior probe calibration, is required to extract temperature data from the raw sensor resistance data. A simple way to calibrate is to submerse the probe in a well-mixed, thermally insulated, temperature variable water bath and note the resistance for a wide temperature range. The water temperature can be determined accurately using a commercially produced, precalibrated, platinum or mercury standard temperature probe with accuracy specifications from the NBS, submersed in the same bath. The probe should be calibrated over the entire temperature range of possible logging situations. Commercial tools generally will be precalibrated and supplied with their own processing software. Field checks on calibration with an ice bath are easy and important. The ice bath should be prepared with a slush of ice and water with the ice just floating in the water. The temperature will be between 0.01 and O.OOI°C even iftapwater is used to prepare the bath.

Convection

Some effort has been made to develop a logging tool that measures the temperature of the surrounding formation, and not that of the bore fluid (for example, the nuclear logging tool evaluated by Ross and others, 1982) but instruments in use at this time measure the temperature of the fluid. Theory and empirical evidence show that in general the equilibrium temperature of the well fluid is that of the surrounding strata with no correction necessary even for a cased and cemented well (see Diment, 1967). However, a vertical column of fluid with temperature increasing with depth may experience a convective disturbance to the equilibrium formation temperature. The earliest examination of this possibility within boreholes was by Hales (1937), in relation to geyser eruptions. His results suggest that for any borehole with temperatures above 4°C there is a critical thermal gradient, above which convection may be expected in the bore fluid. He determined the critical gradient to be inversely proportional to the fourth power of the hole radius. For a water-filled borehole at 95°C (203°F), the critical gradient is (Jeffreys, 1937):

or 0.0014 az =-r-4-

where r and z are measured in centimeters. The coefficient on the right is viscosity dependent, decreasing for higher temperatures and increasing to 0.014 for water at 20°C (68°F). The theory was tested subsequently and defended by Auld (1948). It is apparent that, even at surface temperatures, normal geothermal gradients (25°C/km; 1.37 °FIlOO ft) should induce


convection in water-filled wells with radii greater than about 2.5cm (1 "). In wells with other types of fluids conditions may be different; for example air and oil may be more stable (Sammel, 1968), but require slower logging speeds because they are less efficient at dissipating heat from the probe.

Interest in the problem reappeared some years later, when Diment (1967) reexamined the model and added an extra term for the adiabatic temperature gradient, which Hales (1937) had discarded as insignificant. Results were virtually identical for most realistic situations. Gretener (1967) tested and confirmed Diment's theory. Sammel (1968) also investigated convection in wells with similar results. All of these results implied that in regions of average thermal gradient, the fluid column in wells of radius greater than 2.5cm (1 ") filled with water probably is convecting.

These findings could be interpreted to cast doubt on the validity oftemperature data from virtually every borehole ever logged. In most situations, however, although convection may be present within a fluid column, the magnitude of the gradient disturbance caused by convection cells is determined to be small. The detailed correlation of lithology (other geophysical logs) to thermal gradient logs at the I-meter level empirically proves that in practical situations natural convection is a minor problem. Several studies (e.g. Wisian and others, 1998; Gretener, 1967; Diment, 1967) have noted that even for boreholes larger than critical radius, convection cells do not extend more than several well diameters in height, and have little effect on the overall logged temperature profile on a meter scale. Empirical measurements in a large diameter geothermal well (18 cm, 7 in) with high and variable thermal gradient by Diment and Urban (1982) showed that the amplitude of the induced temperature fluctuation at a particular depth is proportional to the thermal gradient, but that even at gradients as high as 278°CIkrn the meter scale gradient was not changed (see Fig. 3).

Thus, we conclude that generally convection within a water-filled wellbore will increase noise without significantly disrupting broader temperature gradient patterns. Regions of higher gradient will yield noisier logs, as will sections of open holes that may have been washed out, thus increasing the effective radius. The convection induced in large diameter washout areas in open holes is another reason for the general low quality of open-hole temperature logs (Blackwell, Murphey, and Steele, 1982).

Precision Thermal Gradient Logs

Examples of precision thermal logs that illustrate a variety of the points discussed here for petroleum settings are illustrated in the following sections. The temperature gradient log is of more interest than the absolute temperature because gradient is the parameter required for determining heat flow. There are a number of finite difference methods for estimating gradient from discrete depth-temperature data. The simplest is to take the temperature difference between two successive data points and divide it by the depth difference, assigning the resultant gradient to the depth of either datum. This is known as a forward or backward difference, depending on whether the gradient is equated with the upper or lower depth. Discretization error is reduced if we use the average of the forward and backward differences at each temperature datum. This is known as a centered difference because each gradient estimate is centered upon a specific depth datum. Once the depth-gradient log has been produced, it may be necessary to filter high-frequency noise from the record. Generally, for the logs described here, a 5-11 point mean or median filter is sufficient to clean up the record and remove spurious spikes from the gradient log.


TIME (MINUTES)

0 10 20 30 50 60

.10

.05

0

-.05

-.10

~ w

"" :::> .05 !;t

III a.. ~ t-

0

-.05

.05

0

-.05 .02

0 .02

·.02 0

·.02 5

Figure 3. Amplitude of temperature oscillation with time as function of mean thermal gradient in large diameter geothermal well (East Mesa, California #31-1, Diment and Urban, 1982). Recordings are arranged in order of decreasing thermal gradient from 278 °CIkm (1), to 178 °CIkm (2), to 103 °CIkm (3), to 37 °CIkm (4), to 8 °CIkm (5). Probe was centered in well and time constant was about 2 seconds.

WEST RANCH FIELD, TEXAS

In 1983, precision temperature logs were recorded for two wells in the West Ranch field, near Vanderbilt, Texas (Fig_ 4, Table 1). The wells, #493 and #496, are separated by a distance of about 1.0 km (0.6 mile). The data were recorded from the surface to a depth of approximately 1830 m (6000 ft) in each well, with a temperature resolution of 0_001 °C, depth increment of 1.Om (3.3 ft), and a logging speed ofO.06ms-1 (12ft/min). Both wells were drilled in the fall of 1981 (drilling took about 1 month for each well), cased, cemented, perforated in the Frio, and tested. They had remained undisturbed since 1981 so there was more than sufficient time to achieve thermal equilibrium, and therefore these wells represent ideal conditions for precision temperature logging.

The geology of the field has been described partially by Galloway and Cheng (1985)_ The trap for the field is a simple domal anticline with a closure of over 50 m and dimensions of about 6x4 km. The producing section is in a series of transgressive Frio (Oliogene) barrier/strandplain sands and regressive shales starting at a depth of about 1550 m_ The two wells logged are near the top of the structure.


96.55°

Figure 4. Location of West Ranch Field and #493 and #496 wells, Texas Gulf Coast.

A comparison of the temperature and gradient logs from the two wells (Fig. 5) shows a high degree of correlation. The thermal profiles are almost identical down to about 1500 m (5000 ft). The log from well #493 has a higher noise level than the log from #496 so the gradient data were subjected to smoothing using a seven-point (6m; 20 ft) moving average. The data are otherwise as recorded. The large oscillations and some of the differences between the two logs in the bottom portion of the wells reflect the fact that these holes are in an old and productive oil field, with production zones in the sands between 1500-2000 m (5000-6500 ft). The extreme gradient excursions represent remnant production disturbances in the formations (not associated with these wells which were not produced) caused by moving fluids and expanding gas.

The lithologies penetrated by the two wells are dominantly sand and shale. The higher gradient sections correspond to zones that are higher in shale content, whereas lower gradients occur in sand-rich sections. The lowest gradients in both holes, above the potentially disturbed section, are about 18-20°CIkm (1-1.1 °F/100 ft) and occur in intervals of the well where the natural gamma-ray values are 40 to 60 API (see Figs. 6 and 7). Except within the depth range of production disturbances, minimum gradients apparently correspond to clean sands. Gradient highs show more variation with a range of 33-45°CIkm (1.8-2.5 °F/100 ft), tending to increase with depth down to about 1500 m (5000 ft). The corresponding natural gamma-ray values are 70 to 90 API units. The highest average gradients in both wells (outside the depth


Table 1. Location of precision temperature logs described by this paper, Blackwell and Steele, and Carter and others.

Location Longitude Latitude Town/Range Depth Ft. Depth M. Date Logged This paper West Ranch -493 -96.606 28.782 NA 6258 1908 5123/82

West Ranch -496 -96.599 28.789 NA 6241 1903 5123182

Postle-Hough 69 -101.606 36.851 5N113E1-36 6320 1927 10120/81 Postle-Hough 101 -101.650 36.837 4N113E1-3 6055 1846 5/1/90 Postle-Hough 103 -101.656 36.854 5N/13E1-33 6085 1855 4129/90 Postle-Hough 132 -101.659 36.913 5N/13E1-9 6007 1832 4130/90

Spiers -97.845 34.871 5N/6W-28 10950 3339 12111/90

Donehy#4 -122.069 39.565 20NI2W-14 4787 1460 8126/91 Miner Jones -122.069 39.526 20NI2W-33 3109 948 8127/91 Sprague Lewis 49-60 -122.086 39.541 20NI2W-33 5768 1759 8127/91

Sprague Lewis #1 -122.079 39.538 20Nl2W-34 5639 1719 8128/91

Sprague Lewis #3" -122.080 39.540 20NI2W-34 NA NA NA

Blackwell and Steele (1989a) Watson #1 -94.905 38.477 18S123E-18 1915 584 6/9/81 GElS #1/Smokeyhill -97.575 38.872 13SI2W-32 3427 1045 11117/80 SMUWELL -96.782 32.844 NA 2673 815 10/5/82 MWX-1 -107.870 39.233 6S/94W-28 8477 2585 8/9/82 Chapman #1 -96.091 30.184 NA 8199 2500 2114/84 Parker 13-9 -101.500 40.133 2N/37W-9 3608 1100 7130/82 C. Hovland #1 -102.433 48.922 163N/90W-29 5887 1795 9/13164

Blackwell and Steele (1989b) Rooks Co. -99.543 39.245 9S120W-27 3427 1045 11/15/80 Big Springs -95.478 39.013 12S/17E-13 2886 880 11125/81 LK-1 -98.167 38.383 19S/8W-23 751 229 11117n0

LK-2 -98.167 38.367 19S/8W-26 1076 328 11/17n0

Butler Co. -99.972 37.830 25S/4E-34 2417 737 11119/80

Sallyard#9 -96.477 37.833 25S/8E-36 1259 384 11119/80

T.E.Bird -95.923 37.860 25S/13E-24 1446 441 11118/80 Frontenac -94.742 37.457 30S/24E-2 1115 340 1110/80

USGS-BST -95.207 37.330 31S120E-22 1804 550 614180

Carter et al. (1998) Garner -98.473 36.189 21N/15W-10 7071 2156 1131/88 Leforce -97.554 36.435 26NI7W-14 5332 1626 10m87 Frances -97.450 36.130 20N/5W-17 6009 1832 1015/87 Mackey -99.443 35.278 11N124W-4 7166 2185 712187 Cavitt -97.564 35.012 6NI7W-4 7051 2150 1/4188 Ferris -98.090 35.023 7N/9W-28 55485 16918 3/4/88 Perdasofy -98.262 34.498 4N112W-11 2952 900 12126/62

Gosnold et al. (1990) Parker -101.510 40.150 2N137W-9CC 4182 1275 7130/82 Hardy -101.146 40.229 3N/34W-15BD 2493 760 7129/82 Burton -99.579 42.939 34N119W-8AB 2444 745 7122182 " used for conductivity only


E

Temperature,OC o 20 40 60 80 Or-~~-.~~-r.

500

West Ranch #493 & 496

~ 1000 o

1500

2000 '----A---L..---L_'----A-......

Frio Formation

o Gradient, ·C/km

20 40 60

Figure 5. Comparison of temperature and thermal gradient logs from West Ranch wells #493 ( dashed line) and #496 (solid line).

range of production disturbance) are about 40°CIkm (2.2 °FIlOO ft) in the 1420-1500 m (4650-5000 ft) range and this gradient is shown as the "shale" line in Figures 6 and 7. Deeper than 1500 m (5000 ft) it is difficult to discriminate high gradients because of shale content from those because of production disturbances.

The two thermal logs clearly illustrate the reproducibility of high-quality precision temperature data and the one-dimensional thermal regime in this field. Despite a separation of 1.0 kIn (0.6 mile), the measured thermal gradients can be correlated almost point for point on a scale of3 m (10 ft) and the temperatures at the same depth in the two wells do not differ by more than 0.35°C outside the depths of production disturbance. Such close correlation indicates that individual variations in gradient are significant on a fine scale. This important conclusion gives us confidence in inferring relative in situ thermal conductivity values for depth intervals of meters to lOs of meters from precision thermal gradient logs. This result contrasts with the kilometer-scale resolving power ofBHT data. Blanchard and Sharp (1985) have postulated large-scale natural convection in the sands in this field on the basis of an apparent cellular pattern to the BHT's. Based on these two temperature logs, such variations probably are noise rather than signal because the logs in these wells show no evidence of departure from conductive conditions except in the immediate producing zones.

Total gamma-ray logs usually are used to estimate the proportion of shale within a sequence. A high gamma-ray count corresponds to a relatively high proportion of uranium, thorium, and potassium-bearing minerals, which generally implies a clay-rich lithology.

HIGH-RESOLUTION TEMPERATURE LOGS

Gradient, °C/km o 40 80 o r----r-~===r-___,

500

E

~ 1000 Q)

Cl

1500

Production /sturbance

2000 1--....1--1--....1-----1

Gamma Count, API Units Sonic velocity, IJs/m o 50 100 150 200 400 600

Caliper

Sonic

20 40 60 Caliper, cm

Figure 6. Caliper, gradient, natural gamma ray, and travel-time logs for West Ranch #493.

15

Conversely, low gamma-ray activity generally implies a 'clean,' or clay-free lithology. There is a close correlation between the behavior of the thermal gradient and gamma-ray logs for the two wells as illustrated for well #493 in Figure 6. On a fine scale, low gamma-ray activity generally is associated with low gradients within the drillhole. These sections can be interpreted as sands with a low content of uranium, thorium, and potassium and a high quartz content and thermal conductivity (thus a low gradient). Broader trends in gradient with depth,

16

o

500

E

~ 1000 Q)

o

1500

BLACKWELL, BEARDSMORE, NISHIMORl, AND McMULLEN

Gradient,OC/km Gamma Count, API Units Sonic velocity, iJs/m o 40 80 o 50 100 150 o 400 800

Caliper

Sonic

20 40 60 Caliper, cm

Figure 7. Caliper, gradient, natural gamma-ray, and travel-time logs for West Ranch #496.

particularly within the predominantly shale sections, are mirrored on the gamma-ray log. The thick shale unit between 1340-152Om (4400-5000ft) is defined clearly on both logs, although the subsection of particularly high gradient does not have a distinctive gamma-ray signature.

The only significant zones of noncorrelation, above the disturbed region, are between 760-820 m (2500-2700 ft) and 1500-1570 m (5000-5150 ft). In the shallower section, the gamma log shows sand whereas the gradient log shows shale, whereas in the deeper section the gamma log shows a massive shale layer whereas the gradient log shows a more sandy


lithology. Deeper than 1600 m (5250 ft), the gradient log is too noisy because of production disturbances to identify any clear correlation or noncorrelation between the logs.

The results are similar for well #496 as illustrated in Figure 7, except that the quieter gradient log allows a more detailed comparison. The fine-scale correlation between the gradient and gamma-ray logs is particularly clear in the upper part of the well where rapid variation in lithology has point-for-point correspondence on the two logs. Again, though, there are zones of noncorrelation between 760-820 m (2500-2700 ft) and 1500-1570 m (5000-5150 ft). The gamma-ray log shows that the main shale unit is thicker than the gradient log shows.

These results show that gradient logs are as sensitive at least as gamma-ray logs in distinguishing between sand and shale units. In regions where the two logs do not correlate, there is no way of determining which is the more reliable indicator without confirming lithology by some other methods.

One may expect a similar correlation between sonic velocity and temperature gradient, because shale has the longest travel times and the highest gradients. However, this relationship generally is valid only at shallow depths. Compaction effects cause velocity to increase with depth faster in shale than in sand, so that travel times in the two lithologies converge and eventually coincide. It is interesting to note that the compaction effect is the opposite for temperature gradient because compaction tends to enhance the thermal conductivity contrast between lithologies by reducing the low-conductivity water content in the sand.

It is immediately obvious from the logs (Figs. 6 and 7) that the velocity distinction between lithologies is diminished markedly below about 1200 m (4000 ft). This is particularly obvious between 1200-1650 m (4000-5400 ft) in well #496. The sand between 1260-1360 m (4150-4450 ft) has a low gradient, but much of it has high travel times. Furthermore, neither the upper nor the lower contact of the thick shale unit has any expression on the travel time log.

The quality of sonic logs is dependent on the condition of the holes, and there are several depths in these wells at which the hole diameters are abnormal, particularly in #493 (Fig. 6). Unfortunately, these depths tend to coincide with sand units as interpreted from the gamma-ray and gradient logs. As there are only a few significant sand units in the holes, and many of these are washed out, it is almost impossible to establish a value for the sonic velocity of the sands from the logs.

These examples illustrate an important point. Below an arbitrary depth, in a sand/shale environment such as the Gulf Coast it is not possible to deduce thermal conductivity from velocity information alone. With independent lithological data (for example, a gamma-ray log) it may be possible to relate thermal conductivity to lithology and sonic velocity, although in different geological settings the velocity-depth curves for sand and shale will differ. This represents a major limitation for techniques which attempt to calculate subsurface temperature using only seismic data (e.g. Houbolt and Wells, 1980). However, techniques that use multiple logs to determine both lithology and porosity (Brigaud, Chapman, and LeDouaran, 1990; Griffiths and others, 1992) offer real promise if the bulk thermal conductivity values of the various lithologies are known, a problem with the shale lithology.

Another interesting point arises from a comparison of the sonic and gradient logs. The sonic log indicates a gradual increase in the velocity of shale with depth, as would be expected during dewatering and compaction. However, the temperature gradient within the shale remains constant, or perhaps even increases over the same depth range, contrary to the usual assumption in basin thermal analysis (e.g. Funnell and others, 1996), based on the assumption of a constant shale rock-component thermal conductivity and loss of a low thermal


conductivity water component. There are two possible explanations for this observation. Either heat flow increases with depth, so that the expected higher conductivity at depth does not result in a decrease in gradient, or else the thermal conductivity of shale does not increase with compaction (Blackwell and Steele, 1989a). The latter possibility has implications for all shale conductivity models, and is discussed briefly in the conclusion.

Thus gradient logs can be used with other well logs to define zones of similar lithology and contacts between different lithological units. If heat flow is constant, then thermal gradient is inversely proportional to thermal conductivity and the consistent gradients in similar lithologic units indicates constant vertical heat flow in the well. Thermal conductivity is a rock property that primarily is a function of rock composition and porosity, so gradient logs should be sensitive to lithological change, as are other logs such as total gamma-ray count and sonic velocity.

Thermal conductivity measuerments were made on 6 core samples (three shale and three sand) from well #493 in the depth interval from 1307 m to 1867.5 m. The average value for the three sands was 2.62 W ImK and the average value for the three shales was 1.30 W ImK for a ratio of2: 1. Additional thermal conductivity information is available from McKenna, Sharp, and Lynch (1996) who measured thermal conductivity on a nwnber of Frio core samples in the SMU Geothermal Laboratory. They determined an average value for the clean quartzose (>35% quartz) Frio sands with a porosity of 19 to 23% of2.73 W/mK. Clean quartzose sands with a quartz content of <35% had an average value of 2.31 W/mK. A reasonable in situ thermal conductivity of the cleanest sands should be about 2.5±0.1 W/mK with a 5 to 10% temperature effect on the sand. With this value the heat flow for a gradient of 20° CIkm would be about 50 m Wm-2 whereas for the gradient of 40° CIkm in the shales and a thermal conductivity of 1.3 W/mK the heat flow would be about 52 mWm-2• The agreement is close considering the possible errors in the values of thermal conductivity.

ANADARKO BASIN, OKLAHOMA

The Anadarko Basin (Fig. 1) is a foreland basin in Oklahoma, formed primarily in the Pennsylvanian on top of a Cambrian rift basin (see Johnson and others, 1988). The thermal regime in the basin has been explored using detailed lithologic analysis, thermal conductivity measurements, and detailed temperature logs by Carter and others (1998) and Gallardo and Blackwell (1999). Details of some of the temperature logs run there have been described by Carter and others (1998). Two additional areas, one field with four sites and one field with one site, are described here, to illustrate the information they provide on the use of temperature logging in the petrolewn setting.

Postle-Hougb Field

In 1991, precision temperature logs were collected from three wells in the Postle-Hough field in Texas County, near Guymon in the Oklahoma Panhandle. The field is located in the western edge of the Anadarko Basin (Fig. 8; Table 1). All three wells had produced oil and/or gas from Pennsylvanian Morrow sands and were temporarily off production awaiting recompletion or further examination. A fourth well in the field was logged previously in 1981. High-precision temperature data at a depth interval of 0.1 m were collected from all holes to a depth of about 1,800 m (6000 ft). A temperature-depth plot comparing all four wells (Fig. 9) shows the temperature logs to be essentially linear, increasing from a mean of about 15°C


I 13E CRISS-fO km /f

13-2 ~ COLO;;oo-.{ KANSAS

5N 5N I OKLAHO/ ~o,tI.-Ho",h field

36°52.5 /TEXAS I 103 69 . 14y I I I 11~1 I II

13E ~-=-

1 mi 1 km 100° 37.5'

Figure 8. Detailed location map of wells in Postle-Hough field, Anadarko Basin, Oklahoma Panhandle.

400

800 E .t: Q. GI

C 1200

1600

Temperature,OC 20 30 40 50

Postle-Hough Field

60

#103

#13·2

'.

70

2000L-----~----~----~----~----~-----L----~----~

Figure 9. Temperature versus depth curves for four wells in Postle-Hough field.

19

(59°F) at the surface to bottom-hole temperatures of about 60°C (140°F). However, the different logs show detailed structures that are examples of how the quality of a temperature log can be evaluated from internal evidence, because the theoretical effects of the many and different disturbances are impossible to anticipate.

The temperature and gradient logs for well #101 (Figs. 9 and 10) have characteristics that strongly suggest the well was not in thermal equilibrium when logged. The high amplitude oscillations in the gradient log (especially above 600 m; 2000 ft), including several regions of negative gradient, imply that the temperature in this well is not equilibrated to the temperature of the surrounding strata. The section below 1600 m (5250 ft) seems to be the only part of the


200

Gradient °C/km

40 0

400t--~---

600

800

E

~1000 Q)

o

Gradient °C/km

40 0

Gradient °C/km

40 0

Gradient °C/km

40

Gamma Ray API Units

o 100 200

Figure 10. Gradient logs for four wells in Postle-Hough field and natural gamma-ray log for well #13-2. Expected gradient for heat flow of 55 mWm-2 for thermal conductivity values of (1) evaporites, (2) sandstones/limestone, (3) Pennsylvanian and Permian red shales, and (4) pre-Permian marine shales from Gallardo and Blackwell (1999) are shown by vertical lines for #103 and #13-2 wells.

well not dominated by noise on a 10 to 20 m scale. Although the average thermal gradient is similar to that in the other wells, the perturbations in the log render it inadequate for detailed analysis. The parallelism of the temperature curve to the equilibrium ones except in the bottom 100 m of the well demonstrates the heat exchange nature of production disturbances and suggests that the well actually had been producing more recently than thought at the time


of logging. The characteristics that would allow the departure from equilibrium to be recognized if only the one log was available are the oscillatory temperatures and negative gradients, and the lack of detailed correlation (at the scale of 1 to 10m units) to the lithology. The temperature and gradient logs from well #69 (Figs. 9 and 10) indicate that this well was closer to equilibrium, but showed a number of disturbed regions. Between 400-850 m (1300-2800 ft) temperature is elevated with respect to wells #13-2 and #103 (Fig. 9). This type of thermal disturbance typically is seen when fluid flows between two or more zones in an open well. Well #69, however, is cased so the explanation is not so simple. There may be fluid flow either behind the casing or between perforated sections. There are temperature steps and gradient spikes at 1100, 1535, and 1857 m again indicating some nonconductive disturbance in the wellbore possibly the result oflarge-scale, but slow, vertical fluid flow. The overly smooth gradient curve indicates that there was some small flow in the borehole at the time of logging, that the probe sensor cage was plugged, or that there was oil in the well and the time constant of the probe was affected by the low conductivity of oil. This example illustrates how detailed knowledge of the well construction is necessary to explain departures from thermal equilibrium and conductive conditions. In spite of these problems, the larger scale gradient features correlate with wells #13-2 and #103 and the well could be used for lithologic identification in most sections at a 5 to 10 m window with some degraded precision compared to the best logs. For example, zones oflow gradient are evident around 380m (1250 ft), 520 m (1700 ft) and 800 m (2600 ft), as are high gradients in the shale dominated section below 1700 m (5550 ft).

The gradient log for well #103 (Fig. 10) is of visibly higher quality than those of the two previous wells. Although two high amplitude spikes occur (at 880 m and 1290 m; 2900 ft and 4250 ft), noise levels are low. These properties are characteristic of a well close to thermal equilibrium. The only section where equilibrium remains questionable is in the depth range of 850-1 020 m (2800 to 3350 ft) where there are moderate amplitude oscillations that do not occur in the other wells for the same section. The lithology for this well correlates closely with changes in the character of the gradient log based on the correlation of the log character to that of well #13-2 and the changes in gradient near the top of the Pennsylvanian and the Cherokee.

Well #13-2 seems to be close to equilibrium. The only questionable section is between 1000-1130 m (3280-3700 ft) where the gradient log is oscillatory, whereas on the #103 log the same interval exhibits an essentially uniform gradient. The formation picks for this well correspond closely with changes in the nature of the gradient log. Correlation with the gamma-ray log available for the well below 550 m is good on both a broad and fine scale (Fig. 10), except in the questionable section. The areas of higher gradient also have higher gammaray activity. Lower temperature gradients are associated with sections dominated by limestone, dolomite, and evaporites which have lower natural gamma-ray activity. Many of the units are so thin, however, that their thermal signal may be aliased. Near the top of the Pennsylvanian System both wells #103 and #13-2 Show changes in gradient character that are typical of the regional thermal character of the Anadarko Basin (Carter and others, 1998; Gallardo and Blackwell, 1999). Higher gradient (lower thermal conductivity) marine shales occur in the Pennsylvanian (dashed line #4) and lowest gradient (highest thermal conductivity) evaporites disappear below the base on the Permian (dashed line # 1). The highest gradients, associated with in the Cherokee Group shales, can be recognized in all four wells. This section has the highest natural gamma-ray activity as shown on the log for well #13-2.

These four wells are all in the same region and all penetrate the same section. However, there are obvious differences in the character of the temperature gradient logs. The differences


can be attributed to different degrees of thennal equilibration. Some typical features of disequilibrium have been illustrated using these gradient logs. All four wells show at least minor wellbore effects resulting from production and other disturbances. These effects include production heating and a high noise level on log # 1 0 1, spiky gradient zones in #69, and regions with unexplained gradient oscillations in the 850-1130 m (2800-3700 ft) depth range in wells #103 and #13-2. Induced movement of fluid because of production undoubtedly has caused some thennal disturbance to the gradients in the deepest parts of the wells (>1800 m; 5900 ft).

The wells each have intervals with smoother or more noisy gradient logs than other intervals in the well. These variations may relate to the type and stability of the fluid in the wellbore. These particular wells were filled with fluid only days before the logs were run, but this time was sufficient for local equilibrium as indicated by wells #103 and #13-2. So the high noise in #101 indicates that the well had been producing more recently and the wall temperatures were farther from equilibration than in the situation of the other three wells. Possibly the well records were incorrect in this instance or the wrong well was logged by mistake. The close correlation between gamma-ray count and temperature gradient in the two #103 and #13-2 wells gives a strong indication that heat flow is dominated by conductive processes. Thus, the gradient logs give a good indication of the contrast in thennal conductivity between fonnations in this set of wells and the temperature regime in this area.

In this example no samples were available from the field for thennal conductivity measurement. So measurements were made on 8 cuttings samples from a well (Criss) about 10 kIn (6 mi) northeast of the field. The samples range from 1237.5 to 1813.6 m in depth, were predominately limestone in lithology, and have an average thennal conductivity of2.5 W /mK corrected for porosity and temperature. The gradient that corresponds with the lowest natural gamma-ray activity is about 22 °CIkm so the heat flow may be on the order of 55mWm-2•

Typical thennal conductivity values from Midcontinent lithologies from several companion studies are shown in Table 2 (after Gallardo and Blackwell, 1999). The expected gradient for an assumed heat flow of 55 m Wm-2 for the typical thennal conductivity values of evaporites, sandstones/limestone, Pennsylvanian and Pennian red shales, and, pre-Pennian marine shales from Gallardo and Blackwell (1999) are shown by vertical lines on Figure 10 for the #103 and #13-2 wells (see also Carter and others, 1998, figs. 7 and 8).

The top of the Pennsylvanian section occurs at about 1061 m. Gallardo and Blackwell (1999) determined that the average thennal conductivity of the Permian "red shale" section was about 2.0 W/mK and that the average Pennsylvanian marine "shale" had a thennal conductivity of about 1.5 W/mK. The log for the #13-2 well shows an increase in the amplitude of the highest gradient sections above and below about 1061 m in almost exact proportion to the expected difference between the two lithologies. The Chase Fonnation at 796 m is an evaporitic layer as can be seen from the low gradient there. There also is an overall consistency of the predicted and observed gradients and their ratios with the lithology as generally seen on the gamma-ray log verifying the conductive nature of the thennal setting in the field. The gradients in the #103 well are similar except that the gradients in the Pennsylvanian shales are significantly lower than those in the #13-2 well and the gradient log thus is more subdued. There may be a small thennal disturbance present in the well, or some other effect to cause some of the shale sections to have a reduced response on the gradient log.

The gradients and gamma activity corresponding to shales in the Pennsylvanian are about 36 °CIkm and 100 API except at the bottom of the well where the gradients (and the gammaray counts) jump significantly so that the average gradient is about 55 °CIkm in the shales above the producing horizons and the average gamma count is 200 API. If the heat flow


Table 2. Estimated typical thermal conductivity values (W/mK) for Anadarko Basin lithologies.

Lithology Laboratory Inversion Kansas (Carter et al.. 1998) (Gallardo & (Blackwell &

N Avg. Std. Err. Blackwell. 1999) Steele, 1989b) Pennian redbed 0 1.712.0 2.00

Other shale 57 1.47 0.06 1.50 1.26 Sandstone 141 4.01" 0.10 4.21 2.47

Granite wash 5 4.13 0.23 3.35 Limestone 52 2.96 0.05 2.90 2.94 Dolomite 5 4.50 0.24 4.38 4.34 Anhydrite 3 6.68 0.32 4.65 4.65

* Average of 125 samples over 2.8 W/mK. ** 1.7 for Ferris #1-28. 2.0 for most other sections of the basin.

is 55 mWm-2 and the mean shale thennal gradient is 36 °CIkm, then the inferred thennal conductivity would be 1.53 W/mK, identical to the average shale value that Gallardo and Blackwell (1999) detennined from well calibration, for the shales in the Anadarko Basin. Thus the high gradients in the deepest shales imply that those shales have a lower thennal conductivity (about 1.0 W/mK). The apparent thennal conductivity effect may be the result of oil saturation of the shale above the reservoir, variations in shale lithology, or heat-flow changes because of disturbance associated with production. Variations in shale lithology is the preferred explanation because a similar abrupt increase in thermal gradient is seen in wells in the Texas Panhandle that were drilled as test wells and not for hydrocarbon purposes and because the gamma-ray signature changes. This change in the gamnia-ray character suggests a lithologic change. In Kansas, the shale conductivity was detennined to be as low as 1.0 W/mK in darker, more organic rich, radioactive shales such as the Devonian Woodford shale.

Spiers #1

In October, 1990, a precision temperature log with a sample interval of 0.1 m was run to a depth of 3338 m (10950 ft) in the well Spiers #1 in the Chitwood field, Grady County, Oklahoma. The well was completed in 1946 to a total depth of3616 m (I I ,865ft) and plugged back to 3606 m (1 I ,830ft). Last production was in 1984, when the well was producing only two barrels of liquid per day. Within the hole, the base of the Pontotoc Fonnation, which approximately correlates to the base of the Pennianitop of the Pennsylvanian, is at 1583 m (5195 ft).

A temperature-depth log (Fig. II) shows that the temperature increases from about 15.5°C (60°F) near the surface to a temperature of about 80°C (176°F) at 3340 m. The average thermal gradient increases near the Pennian-Pennsylvanian boundary from about 16.5°CIkm, to about 22.9°CIkm in the deeper part of the well. The only section of the log which does not seem to demonstrate a basically conductive thermal pattern is between 2880-3080 m (9450-10,100 ft) where cooling of the well by gas expansion in obvious. Gas enters the well at 2885m (9465 ft), presumably behind the casing, which causes a cooling disturbance as it expands into the annulus. The gas apparently moves down the hole and enters (or has entered in the recent past) the tubing at a depth of about 3075 m (10,088 ft). The interval is evident on the temperature-depth log as a negative spike where the gas enters, and temperatures at each depth in the interval of flow are slightly lower than temperatures interpolated from above and below. On the gradient log (Fig. 11) large-scale oscillations are evident near the gas inflow zone. Presumably, these are the result of convection associated with the high temperature gradients.


The predominantly conductive nature ofthe heat flow in Spiers #1 is demonstrated by a good correlation between the gradient log and conventional gamma-ray and electric logs (Fig. 11). Unfortunately, no single conventional log covers the entire range of the gradient log and the logs are old and uncalibrated. A natural gamma log was run from the surface to around 1830 m (6000 ft), and a resistivity log from 1830 m (6000 ft) to total depth. There is good correlation at the 3-15 m (10-50 ft) scale between the gradient log and the respective wireline logs. In general, shale sections associated with high-temperature gradients have high gamma activity and low electrical resistance. However, it is difficult to make a one to one correlation in many ofthe thin-bedded Permian units (above 1583m; 5195ft). The clearest correlation can be seen in relatively thick shale units whereas many of the sand and limestone units are relatively thin and the thermal signal of individual beds may be below the spacial resolution of the gradient log. For example, about 1275 m (4180 ft) there is a fairly uniform shale bed on the order of 60 m (200 ft) thick which is clearly apparent on both the gradient and gammaray logs. The thermal gradient in this unit is about 20.0°CIkm. The lowest gradients are harder to characterize but generally lie between Il-l4°CIkm. These may be assumed to represent typical sandstone, limestone, and dolomite/evaporite units.

In the rocks of Pennsylvanian age, the shales have average gradients significantly higher than those in the Permian section. Typical shale gradients in the older rocks peak around 30°CIkm. Sands in the Pennsylvanian section, with the exception of the thick Springer-age Primrose Sand are similar to those in the Permian, thin and difficult to distinguish with certainty. However, the undisturbed zones with minimum gradients average about 11-14°CIkm within the same range as for the high conductivity units in the Permian. These zones are predominantly sandstone and the consistancy in thermal gradient implies that the thermal conductivity of sand remains essentially unchanged across the Permian-Pennsylvanian boundary whereas the shales increase in gradient.

The Primrose Sand is a 60 m (200 ft) thick sandbody of Springer age near the base of the well and shows clearly on the gradient log. There is a clear correlation between the resistivity and gradient logs in this section, with the sand having a relatively high resistivity and low gradient. The mean gradient in the Primrose Sand is 11.5±0.2°CIkm.

No thermal conductivity data are available from Spiers #1 or from any well in close proximity. However, the Ferris # 1 well that was logged to 5 km by Carter and others (1998) and used as a thermal conductivity test well by Gallardo and Blackwell (1999) is only 32 km (20 miles) NNW of the Spiers #1 well. In order to produce an estimate of heat flow for the Spiers #1 well, we can use the regional average values of thermal conductivity for Anadarko Basin lithologies from that well. Ferris #1-28 had been shut in for several months when a high-precision temperature log was run (Carter and others, 1998; Gallardo and Blackwell, 1999). The well bottomed at 5601 m (18,376 ft) in the Pennsylvanian Springer Group. A best estimate for heat flow in Ferris #1-28 was calculated to be 39±3 mW/m2 (value range is standard error) from the gradients and thermal conductivity of two sandstone intervals. Conductivity measurements were made on core samples of Marchand Sandstone (Skiatook Group) and a Morrow sandstone (Morrow Group) taken from wells in close proximity to Ferris #1-28. As in the Postle-Hough field the four predicted gradients for the typical Anadarko Basin lithologies are shown on the gradient plot for the Ferris # 1 well in panel 2 of Figure 11 corresponding to the measured heat flow of39 mW/m2•

Shale is the most difficult lithology to characterize in situ because of sampling problems (Blackwell and Steele, 1989a). For example, the laboratory measurements of thermal conductivity published by Carter and others (1998) were made on dry core samples because the shale disaggregated upon saturation. Obviously, these values cannot represent in situ


o

500

1000

1500

E

:5 a. <I> Cl

2000

2500

3000

3500

Tern peratu re °C

o 50 0

\ , \ Ferris \ #1-28

\I \ , , , , \ , , , , , , , , , , ,

\

, , , \ , , ,

Gradient °C/km

20

Ferris #1-28

o

Gradient °C/km

20

Gamma Ray Total counts

o 40 80

Spiers #1 0 20 40 Resistivity, Ohm-m

25

Figure 11. Temperature, gradient natural gamma-ray, and resistivity for Spiers #1 and gradient log for Ferris #1 (Carter and others, 1998). Expected gradient for heat flow of 40 mWm-2 for thermal conductivity values of(1) evaporites, (2) sandstones/limestone, (3) Pennsylvanian and Permian red shales, and (4) pre-Permian marine shales from Gallardo and Blackwell (1999) are shown by vertical lines for two wells.

thennal conductivity as accurately as measurements made on saturated samples. The inversion technique, using interval thennal gradients to deduce the conductivity contrast between different lithologies, should give a more accurate estimate of in situ conditions. The process


confirmed that typical Permian redbed shales have a higher thermal conductivity than the marine shales in the older section as already seen in the Postle-Hough field and for the Anadarko Basin in general (Gallardo and Blackwell, 1999).

As was done for the Postle-Hough and the Ferris #1 wells, the gradients for the four lithologic groups for a particular heat flow, in this situation 40 mWm·2, are plotted on the gradient log for Spiers # 1 in panel 3 in Figure 11. Three categories of lithologies, excepting evaporites, correspond to the three categories of gradients in the well and the "red shale" marine shale thermal conductivity contrast is seen clearly near the PermianlPennsylvanian contact. The value given in Table 2 for evaporite represents the in situ thermal conductivity for a composition of 70% anhydrite and 30% redbed. The mud log for Spiers #1 notes only minor amounts of evaporite in the Permian section, which is typical for the southeastern part ofthe basin and there are no gradients that match curve 1, the theoretical evaporite gradient, in the well.

The relative values ofthe temperature gradient in different lithologies should be inversely proportional to the thermal conductivity values. Thus, the gradients in the Permian redbeds should be about 0.75 ofthose in the Pennsylvanian shales, and the gradients within the sands should be 2-3 times those in the shales. These ratios are close to those actually observed on the Spiers #1 gradient log. Heat flow in Spiers #1 is apparently about 40 mW/m2, consistent with the results for Ferris #1-28 of39±3 mW/m2.

WILLOWS-BEEHIVE BEND GAS FIELD, CALIFORNIA

The Willows-Beehive Bend field produces gas from Cretaceous sands and is located in the northern part of the Sacramento Basin in central California (Figs. 1 and 12). The geologic section consists mostly of shale and clay-rich arkose and graywacke. All rocks shallower than about 450 m (1500 ft) are continental and post-Eocene in age. A thick Eocene valley fill, the Princeton Gorge, crosses the marine Eocene shale dominated section in the area of the field, with a base at about 1080 m (3600 ft) in Sprague Lewis #1. Below this unit are the gashosting, intertonguing marine, upper Cretaceous deposits of the shale dominated Kione and coarse clastic Forbes Formations. The contact is about 1280 m (4200 ft) in Sprague Lewis #1 and the base of the Forbes is just below the maximum depth ofthe log. Temperature logs were made in August 1991 in four wells in the field, all roughly along strike and spanning a distance of about 5 km (3 mi, see Table 2 and Fig. 12). All had been in production but were temporarily off-line awaiting recompletion or further examination. There was not much log information in this field with only a SP log available for the Sprague Lewis #1 well.

Conditions differed between wells at the time ofthe survey. Doheny #4, about 5 km north of the other three wells, was logged openhole with no surface pressure control, but its producing section was isolated with a plug. The other wells were logged using surface pressure control equipment but the wells otherwise were open to the bottom. The two Sprague-Lewis wells had significant shut-in pressure and the gradient logs were noisy. All of the wells had been topped with water several days before the survey.

Doheny #4 exhibits a strong thermal disturbance within the top 150 m (500 ft). It seems that the fluid within this zone may have been disturbed just prior to logging. No explanation for the disturbance was put forward by the logging party, and it remains unexplained. The gradient log is unusable within this top section but the remainder of the log seems stable and reliable.


:z a: .. x

NORTHERN SACRAMENTO

BASIN, CALIFORNIA

~ .. , ..... OUTCROPS OF uPPER CRETACEOUS STRATA

FORBES GAS FIELDS

EDGE OF FOOTHilLS

OTHER GAS FIELDS

# CITIES

Figure 12. Location map of Willows-Beehive Bend field, northern Sacramento Basin, California.

27

The temperature and gradient logs for Sprague Lewis #49-60 (Figs. 13 and 14) indicate two zones about 1550 m (5100 ft) with reduced temperature and negative gradient. The nature of these thermal disturbances is typical of the cooling effect of gas expanding into the wellbore. Although this well was capped the producing zones were open to the formation. Either the gas-bearing formations produced some gas during, or just prior to, the logging run or the expansion during the production of the well has cooled the formation well away from the well. The upper half of the gradient log is noisy and a 31 point averaging filter was used for the curve in Figure 14.

The temperature logs show nearly linear temperature-depth curves for all wells (Fig. 13), increasing from a mean annual surface temperature of 18°C (65°F) to about 50°C (122°F) at 1700 m (5600 ft). Unlike the previous examples the temperature logs indicate some lateral thermal changes in this field as the Miner Jones #1 and Sprague Lewis #1 wells are about 2°C hotter below 1000 m than the other two wells. The gradient logs (Fig. 14) are all noisy, probably because of the recent disturbance ofthe well fluids, and required more filtering prior to display. A 3-meter median filter followed by a 3-meter average filter was sufficient to reduce noise in all situations except Sprague-Lewis #1 as mentioned next. Within individual formations, the sand units typically have only 30-40% quartz with the remainder of the coarse clastic component composed of feldspar and rock fragments of metamorphic and volcanic provenance. This lack of high thermal conductivity quartz in the coarsest units explains the lack of gradient variation because of the lack of major conductivity variation. The gradients in the wells generally are between only 15 and 20 °CIkm.

28

10 0

200

400

600

E 800 .c ii GI 1000 C

1200

1400

1600

1800

BLACKWELL, BEARDSMORE, NISHIMORI, AND McMULLEN

, , ,

Willows-Beehive Bend

50

Miner Jones #1

Doheny #4

Sprague Lewis #1

Sprague Lewis #49-60

, , , " '-

' ... , ...... """',

60

Figure 13. Temperature versus depth for four wells in Willows-Beehive Bend field with detailed temperature logs.

There are zones within Sprague Lewis #1 that stand out on the SP log (Fig. 14), in spite of the homogenous nature of the formations. The SP log in the interval between 800-1250 m (2600-4100 ft) shows significant variations that correlate with the general character of the gradient log, that is zones with lower SP, probably the sandier zones, have lower thermal gradients. That depth range, along with a similar zone between 1500-1650 m (4900-5400 ft), coincides with packets of coarse clastic deposits that invade a dominantly shale environment. The gradient log in this well was noisy and required an unusual amount of smoothing (45 point average of 0.3 m data) so the gradient log in Figure 14 is averaged more than the other logs making detailed correlation with the SP log more difficult. A minor production disturbance is present in the vicinity of 1500 m.

The mean thermal gradients for all four wells and a number of smaller intervals from Sprague Lewis #1 are presented in Table 3. The mean gradients for the four wells range from only 18.0±0.2 °CIkm for Doheny #4 to 19.7±0.2 °CIkm for Sprague Lewis #49-69 (about LOU OF/100ft). The gradients are low and show little vertical variation, in contrast to the wells in the Midcontinent and Gulf Coast illustrated previously. The lithologies in these wells are "impure" and difficult to characterize in terms of sand, shale, etc. This type of lithology variation probably is characteristic of many continental margin settings, particularly active ones, and the in situ thermal conductivity will be difficult to characterize on cuttings samples alone.

Thermal conductivity measurements were made on 20 core samples from both Sprague Lewis #1 and nearby Sprague Lewis #3. The divided bar technique (e.g. Blackwell and Spafford, 1987) was used to measure thermal conductivity of the cores at 21°C (70°F). Most samples were from clastic rocks with sand-size grains, but a small number of shale samples allowed representative measurements in all major lithology groups. Many of the samples proved unsuitable for the divided bar technique. The shallow samples were poorly consolidated


E .c C. CD o

Gradient, ·C/km

10 20 30 Gradient, C/km Gradient, ·C/km Gradient, ·C/km

10 20 30 SP, mV

50 100 Or-'-~--~'-~--r-~-r~~.--r-.r-~-r~--T"~~

200

400

600

800

1000

1200

1400

1600

10 20 30 o 5 10 Figure 14. Thennal gradient logs for four Willows-Beehive Bend wells and SP log for Sprague LeWis #1. Dashed lines at 14.5 and 20 0C/km correspond to predicted gradients for heat flow of 28 mW/m·2 and thennal conductivities of2.0 and 1.4 W/mK.

and some samples with pebbles disintegrated because the strength contrast between the grains and matrix was too great.

Sandstone porosity shows a weak depth dependence. Shallower than about 1200 m (4000 ft) the pore volume is consistently around 28-30%. Deeper than about 1600 m (5300 ft), however, the average sandstone porosity drops to about 23%. Overall, the shale is less porous than the sandstone. The average thenna! conductivity for six saturated sandstones above 1200 m (4000 ft) is 1.92±O.08 W/rriK. For the five saturated sandstones below 1500 m


Table 3. Interval gradients for wells and calculated heat flow for intervals within Sprague Lewis #1.

Well name Depth interval Gradient Conductivity. Heat flow (m (ft]) (OCJkm) {WInU9' (mW/m2)

... _ .................. QQ~.!:!.11..!~~L ......... _ .. __ ._._¥.±-li~2!!!.~m.:L ..... _!~~Q .. !.l1.L .. ___ ... ____ ... _._._. __ ._. ___ . ____ ._ .. _ .. _ ..

...... _._ ... _.M.i!!.!:r.lp.!!~.!~L._ .. _ .. _. ___ l?.~2.!!ill.OO-ll9!tL ....... _.12.:1..:t: 0.2 _._ .. _._._._ .. ___ .. _____ ._ .. _._. __ _

.......... ~p..!"!!&!1..!: •. ~~!~_~?..:§Q. ... _._._.J.~~~737!!!.~5l.Qg.J ... _ ....... !2.1_.:t:.9:.L __ ._ .. _ .. _. __ . ___ . _____ ._. __ .. _. __ Sprague Lewis #1 488-724m (1600-2375'] 18.8 ± 0.2 1.4 26

808-847m (2650-2779'] 19.9 ± 0.2 1.4 28 847-914m [2780-3000'] 14.6 ± 0.2 1.73 25 884-917m [2900-3010'] 14.2 ± 0.2 1.79 25

1067-1103m [3500-3620'] 18.8 ± 0.2 1.82 34 1104-1182m [3621-3879'] 18.4 ± 0.2 1.82 33 1280-1539m [4200-5050'] 20.2 ± 0.2 1.4 28 1618-1661m [5307-5450'] 21.0 ± 0.2 1.4 29 ___________________ 1~~UQL~~2~~~J ____ J2J ________ ~~ _________ 1~ ___ _ 152-1219m [500-4000'] 17.7 ± 0.2 [1.6] [28]

1402-1448m [4600-4750'] 16.6 ± 0.2 [1.7] [28] 1463-1478m [4800-4850'] 29.5 ± 0.7 [0.95] [28] 1485-1494m [4871-4900'] 19.7 ± 1.3 (1.4] [28] 1494-1509m [4900-4950'] 27.3 ± 0.5 [1.0] [28] 1219-1719m (4000-5641') 21.1 ± 0.2 (1.3) [28]

Conductivity values in (bIllCkels] are inferred values for a heat flow of 28 mW/m'.

(5000 ft), the value is 2.10±0.10 W/rnK.. The average of three shale cores from 844 to 1745 m in depth and with porosities of 2.13 to 2.41 gmlcc is 1.40 W/rnK.. Thus the shale conductivity values are almost identical for samples with widely different densities. These figures also are consistent with the only moderately higher thermal gradients observed in the shale sections. Based on the thermal logs and the limited measurements, shale conductivity in the Willows-Beehive Bend Field seems little affected by porosity (depth). The relative magnitude of the thermal gradient in different lithologies should be inversely proportional to the thermal conductivity values. Thus, according to these limited lab measurements the thermal gradient in the shale should be about 1.4 times that in the sandstone.

Coarse clastic units may represent the most reliable intervals for determining heat flow because of the difficulty in evaluating the in situ thermal conductivity of the shale. However, the thickness and geometry of these units in this field is not ideal. Sandstone generally has thermal conductivity about 3-4 W IrnK. as a result of its high quartz content. The conductivity values of about 2 W/rnK. for the Willows-Beehive Bend sandstones are the result of both high porosities and a lack of quartz. The slightly higher thermal conductivity of the deeper sands can be attributed to lower porosity values.

In many sedimentary basins, shale is the most abundant rock type, and because it has low ~hermal conductivity it tends to control the thermal structure of the basin more than any other lithology. In this part of the section in the Sacramento Basin, however, there is not a major thermal conductivity contrast between sandstone and shale (at least within the logged depth range) so the shale effect is not as dominant. The gradient logs show only small variations with lithology when compared to the other settings described here.

Average thermal gradients for intervals around each thermal conductivity sample that seemed to represent the lithology of that thermal conductivity sample were combined with the measured thermal conductivity to determine interval heat flow within Sprague Lewis #1 (Table 3). Some of the intervals were selected to correlate with the depths sampled in Sprague Lewis #3. Sandstone conductivity in the bottom part of the well was decreased by 5% to allow for the temperature effect. The heat-flow values are calculated from the product of the thermal conductivity and the least-squares fit to the temperature-depth curve in the intervals listed. The statistical uncertainty can not be calculated for individual intervals because there is no way to assess the error in the thermal conductivity. However, the uncertainty in the heat flow value for the entire well can be evaluated based on the spread in the interval heat-flow values. The


best estimate of heat-flow for the well is a depth weighted average of all values, 28±3 mW/m-2•

The mean gradient for Sprague Lewis #1 between 500-1720 m (1650-5640 ft) is 19.0°CIkm. If the section is considered to be 25% sandstone, then the mean thermal conductivity is about 1.5 W/mK. The similarity of the gradients in the other three wells, suggests that heat flow should be similar in each.

It is possible to use the mean heat flow to estimate thermal conductivity in zones where samples are not available. This inverse calculation is particUlarly useful for characterizing intervals where sampling is difficult or problematical, such as shales, and to identify zones in the well of possible nonconductive behavior. The thermal gradient across the shale interval can be estimated and the heat flow can be used to solve for the shale conductivity. The results can be cross checked against lithologic or log information if available or used to characterize the thermal conductivity for whole formations where sampling is difficult or nonexistent. This procedure was used in several sections of Sprague Lewis #1 and the results are the conductivity values in square brackets in the bottom part of Table 3. Of particular note are the low values in two zones between 1463 m (4800 ft) and 1494 m (4900 ft). The low values might be the result of shale lithology or perhaps areas where the effects of gas in the pores reduce the conductivity. Dashed lines at 14.5 and 20 °CIkm are shown on Figure 14 for each gradient log. These correspond to a heat flow of 28 m Wm-2 and thermal conductivities of 1.4 and 2.0 W/mK.

The heat flow in this field is low compared to the global average. In a nontectonic setting such a low heat flow might suggest a large-scale deep aquifer transporting heat away from the region. However, the low heat flow in the Sierra Nevada Mountains and the Great Valley of California is a crustal effect resulting from the cooling effects of subduction beneath this area as recently as 5 Ma (Blackwell, 1971). The cooled crust is heating up at this time and the rapid rise of the Sierra Nevada Mountains is because of the associated thermal expansion. A thermal model for the region was discussed by Saltus and Lachenbruch (1991).

CONCLUSIONS

The general points and conclusions of this paper are: (1) Temperature gradient logs make useful lithology indicators. Of the abundant

lithologies, shale exhibits the highest thermal gradients, whereas sands and carbonates generally have low gradients. Because most sedimentary basin settings are one-dimensional and, at least, locally conductive, a good correlation should exist between an equilibrium thermal gradient log and other lithological indicator logs such as gamma ray and sonic velocity.

(2) A poor correlation between sonic velocity and temperature gradient indicates that it is not possible to calculate thermal conductivity based purely on seismic velocity. Some independent lithological indicator (such as a gamma-ray log) is necessary to draw any relationship.

(3) The information described in this paper supports the findings of Blackwell and Steele (1989a, 1989b) that the conductivity of shale does not increase with depth-increase/porositydecrease, as would be expected from a simple compaction model. The explanation they proposed for this lack relates to the anisotropic thermal conductivity of sheet silicates. Clay platelets have higher thermal conductivity parallel to the plates compared to perpendicular. At shallow depths, clay platelets are oriented randomly and heat can be transmitted along the plates of many clay particles. However, the high porosity also lowers the overall thermal


conductivity of the mud because of the high water content. With increasing depth 90mes compaction. Clay particles progressively rotate towards the horizontal, so that vertical heat flow must increasingly traverse through the low conductivity axis of the platelets. This effect offsets the conductivity increase resulting from water loss. Thus, the conductivity variation with depth for shale may be relatively small even after large porosity changes.

(4) A thermal gradient log from a well not in complete thermal equilibrium will exhibit such features as high noise level, spikes, and regions of high-amplitude oscillation. A gradient log that closely correlates with the gamma-ray log (or other lithology sensitive type oflog) for the same depth range, has a low noise level, and no spikes or steps is likely to represent equilibrium thermal conditions in a conductive setting.

(5) Precision temperature and gradient logs can yield fine-scale information about fluid movement within a well, including the location of entry and exit points, and regions of gas production and expansion. These data may be unavailable by any other method.

(6) Continuous precision gradient logs allow thermal conductivity measurements from specific depths to be associated with specific thermal gradients. This allows a number of heatflow estimates to be made in anyone well, and a weighted mean can be used as a best estimate for the entire well. Also, once a heat-flow value is know for a well, it can be used in intermediate zones to obtain a best estimate of thermal conductivity. This is one way of investigating in situ conductivity of formations that are difficult to sample.

(7) Technology changes indicate that the equipment for making precision temperature logs in a petroleum setting is more available than ever before, making it possible to add the sort of information described here to the thermal aspect of basin analysis and to understand the details of the thermal structure of sedimentary basins in a way not possible in the past.

(8) A low heat-flow value of 28±3 mW/m-2 was determined for the Willows-Beehive Bend gas field in the Sacramento Valley of California. This value is consistent with the low heat flow in the Sierra Nevada Mountains to the east and is the result of the residual thermal effects of the subduction that ended in this area about 5 Ma.

ACKNOWLEDGMENTS

The logging and thermal conductivity measurements were supported by contracts from Mobil Research Laboratories to the SMU Geothermal Laboratory. Robert E. Spafford did most of the logging although some was done by John L. Steele. We thank Mobil Technology Company for permission to publish these results.

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