Avo Inversion Le

This case study reviews the workflow and the resultsachieved in terms of updated development drilling plansfrom a 1500-km2 prestack inversion project over a WestMediterranean Deep Marine Concession in the Nile Delta.Four successful exploration and one appraisal well have beendrilled to date on this concession. Figure 1 shows the loca-tion of the concession (red box) in the offshore Nile Delta,and indicates the locations and field names of the discov-eries to date. The 3D survey over this concession wasrecorded using long offsets (6000 m). Information containedin these offsets has been used to try and obtain rock prop-erty estimates that may help distinguish lithology and fluidtypes in order to high grade drilling locations and helpbuild more reliable reservoir models.

The main inversion objective was to improve the exist-ing reservoir model to help create an optimum developmentplan for the gas-charged complex of channel and levee sandsdiscovered in the block. This was enabled by the generationof 3D cubes of three elastic parameters: P-impedance,Poisson’s ratio, and density. These data were then used toderive additional 3D cubes of petrophysical parameterssuch as water saturation and net-to-gross.

Successful seismic inversion requires a high signal-to-noise ratio and a wide bandwidth. In this case study, ahybrid inversion technique was used to derive the seismicattributes. The technique combines full waveform prestackinversion and three-term AVO inversion. The project wasfocused only on the Pliocene interval where gas-charged type3 AVO sands are present; it was not considered reliable forthe Miocene and below where the sands are deposited belowa high-velocity anhydrite layer. To date, the Pliocene has beenan amplitude-supported play in the area (Figure 2), and thisapproach had a 100% drilling success rate (five out of five).However, it was clear that amplitudes alone did not pro-vide the complete story and we will provide evidence of thatin the course of this study.

Rock physics summary. Adetailed rock physics analysis wasconducted using the extensive log suites from the five exist-ing wells. The sandstone reservoirs are Pliocene, depositedas channel sands and levees. The channel sands form high-quality reservoirs showing high amplitude and a type 3AVO response. The levee deposits are laminated and seis-mically transparent. Depth of burial is 3000-5000 ft belowmudline for all five wells. Therefore, compaction effects arequite large over relatively small depth intervals. The com-paction trends were estimated for P- and S-impedance anddensity, and subsequently removed to allow a depth-inde-pendent analysis of the lithologies.

Historically, our industry has not estimated in-situ gassaturation accurately. The problem originates in the non-linear effect that gas saturation has on seismic data in high-porosity clastics; a small amount of gas creates strong effectson P-velocity and reflectivity. Density change is linear as afunction of saturation; hence, it is the key to improved esti-mation of gas saturation.

Based on the well elastic and petrophysical data, a mul-

tivariate linear regression was derived for water saturation.It was found that including density, in addition to P-imped-ance and VP/VS, significantly improved the fit.

In this area, the laminated sands are believed to containconsiderable volumes of producible gas. The reservoir-qual-ity sands are interbedded with similar but nonpermeableshales, and the net-to-gross (N/G) is estimated at about30%. Layering is typically on a centimeter scale. The area isrich in iron minerals such as siderite, pyrite, and glauconite,with higher concentrations of these minerals apparently inthe nonpermeable layers. The average grain density is vari-able, but on average believed on the order of 2.75 g/cm3 andthe heavy minerals also exhibit high bulk and shear mod-uli. The combination of a heavy and rigid matrix makes theaverage elastic properties of these moderate-to-low N/Gsediments similar to shales when gas-charged and, there-fore, makes them more difficult to characterize.

Hybrid inversion techniques used to derive key elastic parameters:A case study from the Nile DeltaR. ROBERTS, J. BEDINGFIELD, and D. PHELPS, Apache Egypt Companies, Cairo, EgyptA. LAU, Apache Corp., Houston, USAB. GODFREY, S. VOLTERRANI, F. ENGELMARK, and K. HUGHES, WesternGeco, Cairo, Egypt

86 THE LEADING EDGE JANUARY 2005

Figure 1. West Mediterranean Concession outlined by the red box. Thefour prospects/discoveries targeted by the project are shown.

Figure 2. Red amplitude anomalies indicating channel fan complexes aredraped over a depth structure map; initial drilling targets were selectedwhere these amplitude anomalies have closure.

Three log types were consid-ered necessary for a successful eval-uation of the laminated layers:

• FMI to obtain N/G• anisotropic resistivity to derive

the water saturation (Sw) in thepermeable layers

• elemental capture spectroscopy(ECS) to determine the miner-alogy, grain density, moduli,accurate clay volume, and typeof clay

Previous well calibrationswithin the concession showed thatthe following rock/fluid classescould be discriminated by refer-ence to seismically derived attrib-utes. The approximate values areshown in parenthesis for each class.

• clean gas sands = low P-waveimpedance, low VP/VS ratio(~11 000, <2.2)

• clean water sands = high P-wave impedance, intermediateVP/VS ratio (~16 000, >2.5)

• laminated gas sands = reducedP-wave impedance and VP/VSratio (~13 000, ~2.4)

• shales = higher P-wave imped-ance, high VP/VS ratio (>14 000,>2.5)

Pliocene reservoir complexity.Figure 3 is a good example of whyconventional amplitude informa-tion alone does not tell this story.Well Abu Sir 2X was drilled withthe expectation of finding com-mercial hydrocarbons throughoutthe entire high-amplitude interval.However, the second leg of the highamplitude related interval (seearrow) was associated with lowgas-saturated sand. The reservoirproperties of this sand were simi-lar to the pay sands above it but thegas saturation was half the level ofthe overlying sands. As is known,a small amount of gas createsstrong effects on P-velocity andreflectivity. Low and high gas-sat-urated reservoirs can have similarVP and VP/VS ratios. Density infor-mation would be helpful to distin-guish the two cases; however, variations due to lithology canbe much greater than those associated with fluid changes, and,hence, the latter can be masked. This zone had looked veryprospective from an AVO standpoint, as shown in the near-and far-offset stacks.

This result caused concern that much of the prospectivearea may sit below the established gas-water contact (GWC)as found by Abu Sir 2X. Further work was needed to high-grade or further risk the amplitude-related areas elsewherewithin the field boundaries.

When crossplotting some attributes derived in this study,different fluid saturations clearly plot in different quad-rants. In Figure 4, the crossplotted interval is shown on thewell log on the right (from Abu Sir 2X). The plot on the leftshows clean gas sands in red, laminated sands in orange-green, and wet (brine) sands in blue.

Figure 5 shows a density attribute section derived fromthe surface seismic data with an insert showing the densitycurve from the well log data at Abu Sir 2X. Reds indicatelow density values (<2.0 g/cm3), yellows are intermediate

JANUARY 2005 THE LEADING EDGE 87

Figure 3. Well Abu Sir 2X was expected to find commercial quantities of gas through the entire ampli-tude package illustrated. AVO information (near- and far-range stacks in inset) also supported thispredrill assessment. High gas saturations were found in the upper sand, but low gas saturations wereencountered in the lower sand indicated by the blue arrow.

Figure 4. Crossplot of VP/VS versus P-impedance. Color scale is water saturation ranging from 8% (red)to 100% (blue).

values (2.0 - 2.1), and greens/blues are higher density val-ues (>2.1). When compared to the conventional seismic linein Figure 3, the low gas-saturated sand appears distin-guishable from the conventional pay found above it in AbuSir 2X.

Hybrid inversion workflow. The seismic data were pre-processed using a true amplitude sequence that includedprestack Kirchhoff time migration. The cable length was suf-ficient to allow angles of incidence up to 60° at the reser-voir level. Data quality was deemed very good and wellsuited for three-term AVO analysis.

Figure 6 shows the main components of the inversionworkflow used in this project. It involves combining fullwaveform prestack inversion (run at discrete locations) withmore traditional AVO inversion (run continuously through-out the volume). Three-term AVO is preferable to two-termAVO because it allows the determination of density in addi-tion to P-impedance and Poisson’s ratio. The Pan and Gardner

reformulation of the Aki andRichards AVO equation was usedto invert for the three coefficientsof a second-order polynomial insin2θ. Combining the three coeffi-cients with a background VP/VSmodel results in band-limitedreflectivity cubes for P-impedance,Poisson’s ratio, and density. Thesewere submitted to a full bandwidthinversion, where the seismic ampli-tudes were calibrated to the corre-sponding well data, yieldingabsolute P-impedance, Poisson’sratio, and density cubes. Note thatthe reliability of three-term AVOinversion is subject to true relativeamplitude preservation, appropri-ate higher-order anisotropy move-out correction, effective multiplesuppression, minimal mode con-version in the gathers, and highsignal-to-noise (S/N) ratio in thegather data.

It was observed that the esti-mation of density was significantlyimproved by including angles ofincidence up to 60° in the AVOanalysis. While the uncertainty ofthe density estimate is generallylarger than for the other AVOattributes, the match between theseismically derived density and thewell data is good. This adds sup-port that the derived density val-ues are trustworthy.

Full waveform prestack inver-sion (FWPI) uses a forward mod-eling methodology to transformpseudowells into synthetic offsetdata. A comparison is then madebetween the actual seismic datawith the synthetic data; thepseudowells are updated to opti-mize the match. A genetic algo-rithm, outlined in Figure 7, is usedto perform several thousand itera-tions (perturbations) to find the

optimum elastic parameters to match the synthetic to real data.The initial input is guided by the rock physics model andstacking velocities. In Figure 7, the upper right image showspredicted versus actual results for one FWPI point, with theyellow overlay illustrating the error bars. Density is usuallythe most problematic property to predict accurately. In thisproject, 150 FWPI locations were used, clustered in and aroundthe four prospects/discoveries identified previously on theconcession map. The derived VP/VS trends were used as inputfor the AVO inversion. Together with the well data, thepseudowells were used to build low-frequency models thatwere merged with the band-limited data to create the threefinal full-bandwidth inversion data cubes.

Further petrophysical volumes (Sw and N/G) were sta-tistically derived from the elastic volumes using regressionformulae derived in the rock physics part of the project. Itshould be noted that Sw represents the bulk water satura-tion, which includes nonnet components of the reservoir rock.


Figure 5. Density section extracted over the same line as in Figure 3. Note the different response betweenthe low and high gas-saturated zones.

Figure 6. Hybrid inversion workflow used in this study.

Residual gather flattening.AVO, as implemented in this pro-ject, is a sample-by-sample process and as such it is veryimportant to have flat gathers as input. The intermediate tofar offsets supply most of the density information (anglesbetween 45 and 60°); therefore, the angle gathers must be asflat as possible. Although apparent anisotropic correctionshave been applied to these data (Figure 8 top), there is stillsome uncorrected anisotropy in the data as well as some resid-

ual NMO. The gather data were‘flattened’ using an automatedevent picker that is constrained tobe spatially consistent—this notonly ensures that the structuraldetail provided by the high tem-poral resolution near-angle stack isunchanged before and after flat-tening, but also prevents cycle skipsthat commonly plague automaticpickers. The bottom plot in Figure8 shows the result of applying thisflattening process. In general, thistechnique can be applied to the off-set and resultant angle gathers.

The flattening of the moveoutmeans the kinematic effects ofanisotropy are eliminated withoutexplicit knowledge of the aniso-tropy parameters. However, aniso-tropy will also contribute to anotherkinematic aspect, where the offset-to-angle relationship is increasinglyaffected with increasing offsets.This, together with the dynamiceffect of anisotropy, will affect theamplitudes with increasing offsets.The calibration of the seismic to thewell data helps compensate for theeffects introduced by anisotropy.

Well calibration. In order to decidehow well the AVO seen on theactual seismic data matches thatpredicted from the well logs, com-parisons were made between pre-dicted and actual gathers (Figure9). The match in Figure 9 appearsgood and the comparison (lowerpart of Figure 9) of the seismicamplitude at the top and base reser-voir with the corresponding resultfrom the synthetic amplitude con-firms this. The synthetic modeledresult is shown in red and blue, thereal data in purple and yellow. Notethat three neighboring gathers fromthe seismic data are shown. In gen-eral, the agreement was good andit was decided that global ampli-tude calibration scalars to matchthe seismic AVO with those mod-eled from the well data were notrequired for this project. The resultsfor the predicted versus actual gath-ers around the other four wells wereconsistent with this result.

Well-tie results. Figure 10 showsthe Poisson’s ratio, P-impedance, and density results fromthe well logs (filtered to 70 Hz) in red and the extracted val-ues from the final inversion cubes in blue. Part of the rea-son for the good match is because the low-frequencycomponent came from the well information, but the high-frequency component came from the seismic data.

There are some areas of mismatch in the estimates (e.g.,seismic data from gas sands underestimates the change in


Figure 7. Full waveform prestack inversion workflow and an example result.

Figure 8. Residual gather flattening is essential for accurate AVO analysis. (top) Typical gathers beforeflattening. (bottom) Gathers after flattening.

Poisson’s ratio compared to thewell log data) but, generally, thematch is encouraging. In particu-lar, the density estimates from theseismic data had a good correla-tion with the well data.

Attribute maps. Figure 11 showsmap views of three attributes(amplitude, P-impedance, anddensity) extracted over the non-commercial gas interval aroundAbu Sir 2X. The conventionalamplitude extraction shows anarea of high amplitude aroundAbu Sir 2X which is associatedwith the low gas-saturated inter-val, whereas the density and P-impedance extractions show thisarea to be less prospective. Allthree extractions suggest com-mercial hydrocarbon accumula-tions at the proposed Abu Sir 3Xlocation, which is structurallybelow the GWC found in Abu Sir2X.

Figure 12 is a water saturationmap over Abu Sir Field. The watersaturation attribute is effectively ameta-attribute that uses P-imped-ance, Poisson’s ratio, and densityto estimate the water saturation.Analysis of the seismic attributesderived in this project showed thatusing all three elastic attributes(P-impedance, Poisson’s ratio, anddensity) provided a better matchwith the wells for water saturationcompared to using P-impedanceand VP/VS only. It is felt that usingthese attributes together wouldallow discrimination of commer-cial gas from fizz gas ahead of thedrill bit.

Figure 13 illustrates a practicalresult of the study. The conven-tional amplitude extractions overthe Pliocene interval targeted bythe El King 2X well were compa-rable in strength. Extractions fromthe attribute data indicate the eastern levee should have bet-ter reservoir properties (water saturation is shown in Figure13) than the western levee. Based on this information, thedecision was made to move the proposed location to testthis better interval.

Conclusions. The project has highlighted many benefits of theworkflow outlined, including:

• improved lithology and fluid discrimination• estimation of gas saturation• improved discrimination of low gas saturation by includ-

ing density• reservoir property prediction• constraints on reserve estimates• improved reservoir characterization• optimized field development

The main challenges in further improving the reservoirmodel building process include:

• facies interpretation and calibration• multiattribute volume interpretation• data quality, particularly high-angle (long-offset) seismic

data• relative amplitude preservation through the acquisition

and processing steps• improve the low-frequency model design in geometri-

cally complex reservoir systems• assigning uncertainty estimates to final output products

While no single technology provides all the answers tothe problems geoscientists face, it is the opinion of theauthors that elastic impedance inversion technology pro-vides valuable information that will help our industry


Figure 9. (top) Modeled versus actual data comparison for the Abu Sir 2X well. (bottom) Comparison ofthe picked amplitudes at both the top and base of the gas-charged sand.


Figure 10. P-impedance, Poisson’sratio, and density comparisons forAbu Sir, Al Bahig, and El Maxdiscoveries. Blue curves are predic-tions from seismic data and redcurves are well data.

Figure 11.Amplitude, density,and P-impedanceextractions over thezone indicated inthe well log. Thelarge anomaly in thelower left of theimages is actuallydowndip of thedrilled wells.However, the den-sity supports theinterpretation thatthe downdip areahas high gas satura-tion where well AbuSir 3X is planned.

become more successful, in boththe exploration and developmentphases. The ability to differentiatebetween low gas saturation andeconomic gas is of particularimportance to the industry, andwe think that three-term hybridinversion is a good approach tohelp resolve that issue.

Suggested reading. “Hybrid seis-mic inversion: Areconnaissance toolfor deepwater exploration” byMallick et al. (TLE, 2000). “Wave-form gather inversion and attribute-guided interpolation: A two-stepapproach to log prediction” by Lauet al. (TLE , 2002). “Reservoirdescription using full waveformprestack inversion” by Mallick andBenabentos (TLE, 2002). The BasicEquations of Plane Elastic WaveReflection and Scattering Appliedto AVO Analysis by Pan andGardner (Annual Progress Review 19,Seismic Acoustic Laboratory,University of Houston, 1987). TLE

Acknowledgments: Apache Egypt wouldlike to thank our partners, RWE DEA andBP Egypt, for permission to publish thisarticle. We also recognize Don Westacottfor his efforts to generate the petrophysi-cal estimates that were used in this study,Dave Jennette for his seismic facies analy-sis, Jim Keggin from BP Egypt andManfred Boeckmann from RWE Dea fortheir involvement and assistance to ensurethis project was a success. Apache Egyptwould also like to thank the EgyptianGeneral Petroleum Corporation for theirsupport of this project.

Corresponding author:[email protected]


Figure 12. Water saturation map over the Abu Sir discovery. Yellow/orange indicate high gas saturation,and blue indicates higher water saturation levels. Existing wells are shown with red dots. The proposedwell Abu Sir 3X is shown with black outline.

Figure 13. Water saturation map over the El King Pliocene and Miocene discovery. Based on this map,the proposed well has been moved to target the eastern levee of this channel/levee complex.

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