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Time-lapsMonitorinMark ZumbergHåvard Alnes

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2 OTC 23701

Prior to the first survey of a reservoir, concrete benchmarks (600 kg concrete cylinders with sloping sides for trawl-fishing resistance) are set on the seafloor at those locations predetermined for gravity measurements. They are intended to remain in place for several decades. For each benchmark visit during the survey, the ROV, carrying the gravity package in its hydraulic arm, lands adjacent to the benchmark. It sets the gravity package on top of the benchmark and lets go (the package remains electrically linked to the ROV for power and data link, but is mechanically separated from the ROV for vibration isolation purposes). Operators on the ship then activate the automatic leveling commands and the gravity meters level themselves. Next, data are recorded for 20 minutes. The peak-to-peak seafloor vertical acceleration can attain values as high as 3000 Gal during periods of high ocean wave activity. This noise is very narrow band (centered near 0.2 Hz), fortunately, so 20 minutes is adequate to average away the noise to a statistical precision of less than 1 Gal. After the data are collected, the ROV picks up the gravity package and transits to the next benchmark. The surface vessel follows the ROV during the survey, dynamically positioning itself to remain over the ROV at all times. Because the gravity sensors and the pressure sensors are relative and drift at varying rates during the survey, multiple measurements are made at each benchmark. Several benchmarks are located some distance away from the reservoir to provide stable reference points, unaffected by production. If we assume that gravity and height at all of the benchmarks remain constant (except for tidal effects) during the duration of a single survey, the drift can be computed from the multiple repeat measurements and removed. The number of benchmarks varies among our surveyed reservoirs from a minimum of 8 to a maximum of 86, and a survey (or “campaign”), in which each benchmark is visited at least twice, takes up to two weeks. Comparing the relative gravity and height values between two surveys separated by several years yields reservoir density changes in the intervening period, with the assumption that no changes have occurred beneath the reference benchmarks (which, so far, has proven to be consistent with the measurements). To date we have completed 16 campaigns over six reservoirs; each has been repeated at least once. The data provide information useful for natural gas reservoir management and tracking injected CO2. Analyses The gravity meters and the pressure gauges undergo frequent calibrations. In the weeks prior to the survey, the gravity meters are transported on land between two sites whose gravity values have been established with an absolute meter, providing reference gravity values against which the relative gravity meters can be calibrated. During the survey, the data being collected are immediately analyzed for quality control. The most important component of the data QC is the extent to which gravity values are repeated over the multiple measurements taken at each benchmark during the weeks-long survey. Also important is the level of agreement among the three gravity meters being simultaneously deployed. At least two occupations of each benchmark is typically made, with as many as 10 repeat measurements being taken at a small number of stations. After correcting for meter drift and tides (described below), the value of each measurement (with the mean value subtracted) is plotted as a function of time. The resulting scatter plot of measurements reveals the statistical performance of the gravity meters during the survey. Corrections to the Data Tides. The raw data are of relative gravity and relative pressure. The first step in the data processing is to make corrections to both measured parameters for the effects of tides. For pressure, the tidal corrections come directly from the pressure records collected by stationary pressure recorders which are put in place just before the beginning of the survey and recovered just afterwards. These provide a time series of tidal pressure variations that are subtracted from the ROV-deployed instrument package measurements. For the gravity measurements, we use a tidal model of gravity change computed using the software package SPOTL (Agnew, 1996 and 1997). This computes the effects on gravity from tidal Earth deformation and the associated crustal loading from ocean tides. We take the additional step of using the fixed-station pressure records to compute the direct attraction of a varying water level above the observation points. This methodology has been tested previously with a year long deployment of a fixed-station seafloor gravity meter (Sasagawa et al., 2008). Drift. After tidal corrections are made we compute a drift correction for each sensor (both the gravity meters and the pressure gauges drift with time). This correction is based on the assumption that the tidal-corrected values of gravity and pressure do not change during the weeks-long period of the campaign. All non-tidal changes are attributed to sensor drift (although in a few cases we find and adjust for instrument “tares” or step-changes in the instrument outputs). A variable drift rate is allowed because the drift in quartz sensors is not perfectly linear and depends partly on ambient temperature. Drift rates and a few tares are adjusted to minimize the residuals in repeated measurements.

OTC 23701 3

Benchmark shifts. Using the pressure measurements we can determine benchmark height changes that accumulate from one survey to the next. We have observed such changes at the 10 cm level among many of the benchmarks at one of the shallow fields we survey (Sleipner), where the depth is around 80 m. The height changes are not spatially correlated with one another there. We have not seen similar random benchmark height changes in any of our other surveys where depths are 220 m or more – we postulate that the vertical motions at Sleipner are from scouring of the sediment beneath the benchmarks. Because the survey points there are relatively shallow, currents associated with storms at the surface can be significant. We are confident that the benchmark height changes at that site are real because they produce a slight gravity change as well, and correcting the gravity values for these height changes significantly reduces noise in the gravity differences between repeat surveys. At some of the other fields, we have observed height changes that are spatially coherent. We attribute these to reservoir compaction associated with gas extraction. The data analyses and some reservoir models are described in detail in Zumberge et al. (2008), Eiken et al. (2008), Stenvold et al. (2006), and Alnes et al. (2011). Overall we believe the gravity and height values obtained within a single campaign, relative to corresponding values at reference benchmarks, are precise to 2 to 3 Gal and 2 to 5 mm respectively. Evaluating candidate reservoirs for gravity monitoring As mentioned above, the decision to apply time-lapse gravity measurements to a particular reservoir is guided by the size of the signals that can be reasonably expected in comparison to the achieved precision. In general, broad, shallow density changes are more detectable than deep narrow ones. Also, larger porosity in the formation, allowing more pore space to be filled by water as the gas is removed, yields larger signals. To provide a guide to estimate the potential signal size we present a very simple model of a horizontal, thin, disk-shaped reservoir of diameter D, buried a distance d beneath the seafloor. The reservoir formation is assumed to have porosity p with residual saturation s. Residual saturation is the fraction of the pore gas that is replaced by water during production. We assume that we can track variations in gravity with time with an uncertainty of g. Observed at a point a distance d above its center (on the seafloor), the gravitational attraction g of a disc of thickness t, density , and subtending a half angle is given by g 2Gt[1 cos ]. Given an uncertainty of g, and reservoir parameters p, s, and a density difference , we would like to know what geometry of a reservoir can yield a resolvable signal. Solving the above equation for t we have

t g

2G p s 1d /D

1/4 (d /D)2

.

Here t is the thickness of a disc that produces a signal of g at the observation point when the pore gas is replaced by water (they have densities that differ by an amount ). The cosine term has been replaced by appropriate geometry governed by the disc depth and diameter. Figure 1 is a contour plot of t in meters as a function of the dimensionless ratio d/D (the reservoir geometry parameter) and the product of , p, and s (which we call the diluted density contrast — a reservoir characteristic parameter). This is the density difference between water and gas reduced by the fact that the rock matrix itself doesn’t change in density (to first order) during production (hence the porosity term), and not all of the gas is replaced by water (hence the residual saturation term). In Figure 1 we assume that g = 3 Gal (the detectable gravity change with our current capability). The contour lines, then, show the level of rise in gas-water contact detectable for that reservoir, assuming that the contact horizon extends across the entire disc. As an example, at the Troll field in the North Sea, where we have been making measurements since 1998, values for the parameters are approximately d = 1230 m, D = 21 km, p = 0.3, s = 0.55, and = 900 kg/m3. Plotting the resulting ordered pair of d/D = 0.06 and diluted density contrast ( p s) = 150 kg/m3 shows that a gas-water contact rise of less than 1 m is detectable.

4 OTC 23701

Certainly this model oversimplifies real reservoirs, but it can serve as a guide to classify those reservoirs (or suspected reservoir compartments) that may be candidates for effective monitoring with time-lapse gravity. Other factors must be evaluated as well, including a priori knowledge of the reservoir geometry. Because gravity models are non-unique, it may be difficult to discern which layer is responsible for observed gravity changes in the case of stacked reservoirs being produced simultaneously. Conclusion Time-lapse gravity monitoring has been shown to be an effective means to detect density changes within producing natural gas reservoirs. Density change is a parameter inherent to any simulation model and it can be quantitatively applied, in a very straightforward way, to history matching of reservoir simulation models. This is in contrast to 4D seismic where a highly uncertain (and non-linear) elastic model is needed to relate saturation change to seismic amplitude differences. Our repeated gravity surveys at several reservoirs offshore Norway have already been used to rule out competing reservoir models and will aid in future reservoir management decisions. Acknowledgements We thank Statoil for financing the development of this technique and for permission to publish this work. Statoil and the University of California, San Diego, share ownership of Norwegian patent number 310797, Great Britain patent number 2377500, and United States patent number 6,813,564. References Agnew, D. C., SPOTL: Some programs for ocean-tide loading, SIO Reference Series 96-8, (1996): Scripps Institution of Oceanography. Agnew, D. C., NLOADF: a program for computing ocean-tide loading, Journal of Geophysical Research, 102, (1997): 5109-5110. Alnes, H., Eiken, O., Nooner, S., Sasagawa, G., Stenvold, T., and Zumberge, M., “Results from Sleipner gravity monitoring: updated density and temperature distribution of the CO2 plume.” Energy Procedia 4, 5504-5511 (2011) doi 10.1016/j.egypro.2011.02.536, GHGT-10 Conference, 19-23 Sept 2010, RAI, Amsterdam, The Netherlands. Eiken, O., Stenvold, T., Zumberge, M., Alnes, H., Sasagawa, G., “Gravimetric monitoring of gas production from the Troll field.” Geophysics 73 (2008): WA149-WA154. Sasagawa, G., Zumberge, M., Eiken, O., “Long term seafloor tidal gravity and pressure observations in the North Sea: Testing and validation of a theoretical tidal model.” Geophysics 73 No. 6 (2008): WA143-WA148. Stenvold, T., Eiken, O., Zumberge, M. A., Sasagawa, G. S., Nooner, S. L., “High-precision relative depth and subsidence mapping from seafloor water-pressure measurements.” SPE Journal, II, (2006): 380-389. Zumberge, M., Alnes, H., Eiken, O., Sasagawa, G., Stenvold, T., “Precision of seafloor gravity and pressure measurements for reservoir monitoring.” Geophysics 73 (2008): WA133-WA141.

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OTC 23701

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