Pre-stack Simultaneous Inversion Research Articles

Simultaneous seismic inversion to identify prospective areas in carbonate rocks of the southeastern part of the West Siberian Platform

This paper focuses on the description of a technology and results of identifying and mapping areas in Devonian carbonate rocks prospective for hydrocarbons and associated with increased fracture-cavern porosity in the southeastern part of the West Siberian Platform. The lack of wide-azimuthal seismic data and recording of only the vertical component in the study area did not allow the use of the direct indicators of fracture systems based either on azimuthal anisotropy of the amplitudes of pressure waves or on splitting converted waves into fast and slow. Instead, abnormally low values of the ratio of pressure-wave and shear-wave velocities derived by deterministic simultaneous pre-stack seismic inversion were used as an indirect indicator of increased fracturing. The choice of this seismic signature of fractures is substantiated by a brief review of publications on its successful use in the identification and delineation of highly fractured and cavernous zones in carbonate reservoirs. The behaviour of the indicator showed good agreement with well productivity in the study area and, therefore, made it possible to predict a number of perspective pay zones, presumably associated with in-creased fracturing. At the same time, however, well log estimates of the velocity ratio related to fractured reservoirs exhibited an opposite trend, which mismatched the facts observed in the study area and reported in the literature. This apparent discrepancy is explained by the impact of near-vertical natural macro-fracturing, which, due to different measurement scales, might substantially reduce seismic estimates while producing no impact on well log estimates. In order to describe this phenomenon quantitatively, the weak-anisotropy approximation of P-wave reflection coefficients at a horizontal boundary derived by Rüger for transversely isotropic media with a horizontal axis of symmetry was used. This equation was rewritten in terms of impedances and density and then was analyzed analytically. To express the impact of fractures in terms of fracture density, the simplest model of thin, isolated, penny-shaped fractures was used.

Prospect Identification using AVO Inversion and Lithology Prediction

Identifying prospects within a large study area is traditionally a time consuming process. Schlumberger Reservoir Seismic Services have produced an efficient prospect screening tool in the form of a well log calibrated gas sand probability cube derived from AVO inversion attributes. Pre-stack simultaneous AVO inversion was performed on a 5048 sq/km multi-client seismic survey to compute seismic elastic attributes (acoustic impedance, Poisson?s ratio and density) which can be used to generate lithology and fluid properties. The survey was acquired in 2008 and is located offshore between the giant Io/Jansz and Scarborough gas fields on Australia?s NW shelf, with potential gas reservoir?s situated at multiple levels within a complex geological setting. Well log data from within the survey area were calibrated to the seismic, from which wavelets were estimated for each angle stack using the angle-dependant reflectivity logs. Low frequency models were derived using log data from wells both inside and outside the survey extents, in conjunction with seismic velocities and guided by interpreted horizons. Elastic attribute logs were generated from the wells and used to produce non-Gaussian lithology probability density functions (PDF), which in turn are utilised to generate a 3D gas sand probability cube from acoustic impedance and Poisson's ratio volumes. The gas sand probability cube can be loaded into a 3D visualisation software package where techniques such as volume rendering and opacity are applied to quickly and efficiently screen for potential prospects from which gas sand geobodies can be extracted for volumetric analysis and further reservoir characterisation.

Application of pre-stack simultaneous inversion on the reservoir identification and fluid prediction: A case history of Es2 member reservoir in Shengli Oilfield

Es2 member reservoir of Guojuzi sag is located in the east Bohai Bay Basin in China, mainly composed of beach bar sediments, which are thin and in irregular distribution. Conventional post-stack seismic attributes cannot predict the reservoir effectively, while pre-stack seismic inversion also has difficulties in application for the low SNR seismic data. A number of amplitude preserved processes are taken to obtain high SNR seismic data. Then AVA simultaneous inversion is adopted to achieve elastic parameters. Well log analysis shows that µρ and lower Vp/Vs can be good indicators for our target reservoir, therefore we extract µρ and Vp/Vs attribute sections and slices from the result of AVA simultaneous inversion and have successfully delineate the spatial distribution of Es2 member reservoir, which are in consistent with the known well log data.

Application of structural interpretation and simultaneous inversion to reservoir characterization of the Duvernay Formation, Fox Creek, Alberta, Canada

Simultaneous prestack inversion of multicomponent 3D seismic data integrated with structural interpretation can provide an effective workflow to maximize value for unconventional plays. We outline an integrated workflow for characterizing the Duvernay play in western Canada, an emerging world-class low-permeability unconventional resource fairway. This workflow includes the determination of a time-depth relationship using synthetic seismograms, generation of seismic-derived time- and depth-converted structural maps, and calculation of inversion-based parameters of density and P- and S-wave velocity. The model-based procedure includes poststack (acoustic) inversion, amplitude variation with offset prestack inversion, and joint PP-PS inversion. With these rock properties determined, calculations are made to determine Young's modulus, Poisson's ratio, and brittleness. Faults are mapped based on time slices, isochrons, and correlatable vertical displacements of stratigraphic marker reflections. Significant strike-slip movements are identified by lateral displacement on interpreted geologic features, such as channels and reef edges. Seismic-derived attributes, combined with structural mapping, highlight zones that are conducive to hydraulic fracturing as well as areas unfavorable for development. Mapping of structural discontinuities provides a framework for understanding zones of preexisting weakness and induced-seismicity hazards.

Quantitative prediction of total organic carbon content in shale-gas reservoirs using seismic data: A case study from the Lower Silurian Longmaxi Formation in the Chang Ning gas field of the Sichuan Basin, China

We present a quantitative prediction of total organic carbon (TOC) content for shale-gas development in the Chang Ning gas field of the Sichuan Basin (China). We have used the rock-physics analysis method to define the geophysical characteristics of the reservoir and the most sensitive elastic parameter to TOC content. We established a quantitative prediction template of the TOC content by rock-physics modeling. Well data and 3D seismic data were combined for prestack simultaneous inversion to obtain the most sensitive elastic parameter data volume. According to the prediction template, we transformed the sensitive elastic parameter data volume to the TOC content volume. The rock-physics analysis indicates that the reservoir with a high TOC content in the Lower Silurian Longmaxi Formation (Fm) of the Chang Ning (CN) gas field is characterized by low density, low P-wave velocity ([Formula: see text]), low S-wave velocity ([Formula: see text]), low Poisson’s ratio (PR), and low ratio of P-wave velocity to S-wave velocity ([Formula: see text]). Density is the most sensitive elastic parameter to TOC content. The rock-physics model suggests that density is negatively correlated with TOC content, and the relationship between them changes under different porosities. The reservoir with high TOC content is mainly distributed at the bottom of the Longmaxi Fm and in the central and east central area of the study field. The quantitative prediction results are in good agreement with the log interpretation and production test. Therefore, it has important implications for the efficient development of the shale-gas reservoir in the basin.

Seismic facies-controlled prestack simultaneous inversion of elastic and petrophysical parameters for favourable reservoir prediction

Comprehensive utilisation of elastic and petrophysical parameters to predict favourable reservoirs can help reduce the possibility of misidentification of resources. Existing simultaneous inversion methods for estimating the elastic and petrophysical parameters are typically based on either the Gassmann equation, with which these parameters are inverted from prestack seismic data through stochastic optimisation methods, or Wyllie’s modified equation, with which these parameters are inverted from poststack seismic data using deterministic optimisation methods. The purpose of this work is to develop a strategy for estimating the elastic and petrophysical parameters based on the Gassmann equation using deterministic prestack inversion. We employ the Gassmann equation to construct the relationship between the prestack seismic data and petrophysical parameters. We treat the joint posterior probability of elastic and petrophysical parameters as the objective function under a Bayesian framework. Given the macroscopic geological background and the poor-quality prestack seismic data, seismic facies regularisation constraints were introduced to improve the robustness and accuracy of the inversion. The very fast-simulated annealing method is used to quickly find the optimal solutions for the elastic and petrophysical parameters. Based on a model test and the application of real data demonstrates that the proposed inversion method has high accuracy and strong reliability.

Quantitative prediction of shale gas sweet spots based on seismic data in Lower Silurian Longmaxi Formation, Weiyuan area, Sichuan Basin, SW China

Abstract Sweet spots in the shale reservoirs of the Lower Silurian Longmaxi Formation in Weiyuan 201 Block of Sichuan Basin were predicted quantitatively using seismic data and fuzzy optimization method. First, based on seismic and rock physics analysis, the rock physics characteristics of the reservoirs were determined, and elastic parameters sensitive to shale reservoirs with high gas content were selected. Second, data volumes with high precision of the elastic parameters were obtained from pre-stack simultaneous inversion. The horizontal distribution of key parameters for shale gas evaluation were calculated based on the results of rock physics analysis. Then, the fuzzy evaluation equation was established by fuzzy optimization method with test and logging data of horizontal wells with similar operation conditions. key parameters affecting the productivity of horizontal wells were sorted out and the weights of them in the sweet spots quantitative prediction were worked out by fuzzy optimization to set up a sweet spots evaluation system. Three classes of shale gas reservoirs which including two kinds of sweet spots were predicted with the above procedure, and the sweet spots have been predicted quantitatively by combining the above prediction results with the testing production. The testing results of 7 verification wells proved the reliability of the prediction results.

Application of simultaneous prestack inversion in reservoir facies identification

Poststack inversion is purely acoustic because there is no mode conversion at normal incidence. Therefore, P-wave impedance is the only information that can be estimated from poststack inversion of P-wave data. In full prestack inversion, both the low- and high-frequency components of the P-wave acoustic impedance can be extracted from the seismic data. In addition to the P-wave acoustic impedance, S-wave information or Poisson's ratio can also be estimated from prestack data. This provides fluid information for the reservoirs; thus, prestack inversion has an advantage over poststack inversion. We determined k, KC, m, and mC which are, respectively, the slope of the natural logarithm of shear impedance against the natural logarithm of acoustic impedance, the intercept of the natural logarithm of shear impedance against the natural logarithm of acoustic impedance, the slope of the natural logarithm of density against the natural logarithm of acoustic impedance, and the intercept of the natural logarithm of shear impedance against the natural logarithm of acoustic impedance. We also needed a set of angle-dependent wavelets, which are derived from angle stacks. Hence, we built three angle stacks; the near-angle stack (0–11 degrees), middle-angle stack (11–20 degrees), and far-angle stack (20–29 degrees). Using these angle stacks, we built three statistical angle-dependent wavelets. Finally, with log information we built an initial model for acoustic impedance, and tried to solve the inversion matrix using the conjugate gradient method. By solving this, we could simultaneously derive the acoustic impedance, shear impedance, and density sections from prestack data. Simultaneous inversion used the assumption of a constant shear wave to compressional wave velocity ratio, and the generalized Garnder equation, which are only valid in clastic rocks. The simultaneous prestack inversion method was used for the identification of reservoir facies in one of the hydrocarbon fields in Iran. With this method, four facies were identified; these were confirmed by reservoir geological information and well data.

Seismic reservoir characterization of Utica-Point Pleasant shale with efforts at fracability evaluation — Part 2: A case study

The Utica Formation in eastern Ohio possesses all the prerequisites for being a successful unconventional play. Attempts at seismic reservoir characterization of the Utica Formation have been discussed in part 1, in which, after providing the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, and building of robust low-frequency models for prestack simultaneous impedance inversion were explained. All these efforts were aimed at identification of sweet spots in the Utica Formation in terms of organic richness as well as brittleness. We elaborate on some aspects of that exercise, such as the challenges we faced in the determination of the total organic carbon (TOC) volume and computation of brittleness indices based on mineralogical and geomechanical considerations. The prediction of TOC in the Utica play using a methodology, in which limited seismic as well as well-log data are available, is demonstrated first. Thereafter, knowing the nonexistence of the universally accepted indicator of brittleness, mechanical along with mineralogical attempts to extract the brittleness information for the Utica play are discussed. Although an attempt is made to determine brittleness from mechanical rock-physics parameters (Young’s modulus and Poisson’s ratio) derived from seismic data, the available X-ray diffraction data and regional petrophysical modeling make it possible to determine the brittleness index based on mineralogical data and thereafter be derived from seismic data.

Comparison of model-based generalized regression neural network and prestack inversion in predicting Poisson's ratio in Heidrun Field, North Sea

Drilling wells in the oil and gas industry is a substantial process, whether they are appraisal wells drilled for reservoir-characteristic assessments at the exploration stage or production wells drilled following prior assessments. The challenge has always been to reduce drilling-related expenses and natural/environmental hazards by reducing the number of wells drilled, and to evaluate reservoir characteristics with as few calibration wells as possible. Physical and mathematical modeling of seismic data can help us understand the geologic and structural formations with minimal wells, and interpolate reservoir characteristics across large areas between a few drilled wells. In a new comparative approach, simultaneous prestack inversion and artificial neural network (ANN) methods are used to create 3D Poisson's ratio (PR) models built upon low-frequency initial models (IMs). Training the ANN on IMs similar to those used in the inversion has improved its performance while creating a valid base of comparison between the two methods. The inversion method was able to model the PR around four wells that had been used in creating the IMs. The generalized regression neural network that was trained on a PR IM, along with other seismic attributes, gave results that were consistent with the existing wells. The results of both methods confirm the existence of a strong relationship between PR and known hydrocarbon presence in these wells. However, examining the results with a blind well showed that the ANN was notably more successful than inversion in extrapolating the results beyond the logged sections in the wells and away from control wells. While this particular conclusion cannot be generalized, and the results obtained from the same methodology may vary from one reservoir to another, such results suggest that this procedure can become a robust part of a predrilling reservoir-evaluation phase in developing hydrocarbon fields.

Characterization of shallow high-amplitude seismic anomalies in the Hoop Fault Complex, Barents Sea

The shallow migrating hydrocarbon fluids in the western Barents Sea are usually found to be associated with high seismic amplitudes. We have attempted to characterize such shallow high-amplitude anomalies in the Hoop Fault Complex area of the western Barents Sea. The workflow is devised for discrimination of anomalies that are associated with the presence of hydrocarbons from those that are not, and quantifying them further includes the computation of a set of seismic attributes and their analyses. These attributes comprise coherence, spectral decomposition, prestack simultaneous impedance inversion, and extended elastic impedance attributes, followed by their analysis in an appropriate crossplot space, as well as with the use of rock-physics templates. Finally, we briefly evaluate the futuristic efforts being devoted toward the integration of diverse data types such as P-cable seismic as well as controlled-source electromagnetic data so as to come up with an integrated assessment for the prospects and to mitigate risk.

Quantitative interpretation sensitivity to angle and frequency-dependent pre-stack time shift, amplitude and phase perturbations

As discussed by Long (2017), marine ‘broadband’ signal processing flows typically incorporate a combination of free-surface deghosting, spectral shaping, and attenuation compensation. Overall, there are many opportunities to corrupt the phase content in an angle-dependent and frequency-dependent manner during any signal processing flow, and such risks may increase during aggressive ‘broadband’ flows. We conducted a synthetic modelling study to quantify and understand how angle-dependent time shifts, angle-dependent frequency variations, or frequency-dependent phase errors can impact the recovery of elastic impedance attributes using pre-stack simultaneous seismic inversion. All modelling and inversion was 2D in nature, included no noise considerations, and assumed the velocity model was perfectly understood.

Prestack simultaneous inversion to predict lithology and pore fluid in the Realgrunnen Subgroup of the Goliat Field, southwestern Barents Sea

An integrated multidisciplinary workflow has been implemented for quantitative lithology and fluid predictions from prestack angle gathers and well-log data within the Realgrunnen Subgroup in the Goliat Field, southwestern Barents Sea. We have first performed a qualitative amplitude-variation-with-angle (AVA) attribute analysis to assess the spatial distribution of lithology and fluid anomalies from the seismic data. A simultaneous prestack elastic inversion was then carried out for quantitative estimates of the P-impedance and [Formula: see text] ratio. Probability density functions, a priori lithology, and fluid class proportions extracted from well-log training data are further applied to the inverted P-impedance and [Formula: see text] seismic volumes. The AVA qualitative analysis indicates a class IV response for the top of the reservoir, whereas anomalies from the AVA attribute maps agree largely with the clean sand probabilities predicted from the Bayesian facies classification. The largest misclassification in the lithology classification occurs between shaly sands and shales. A mixed lithology and fluid classification indicates a smaller degree of overlap and allows for the discrimination of hydrocarbon sands. Integration of a qualitative AVA analysis and a quantitative Bayesian probability approach helps in constraining the depositional facies variability within the Realgrunnen Subgroup. Finally, a possible influence of tectonic activity during the deposition of the Realgrunnen reservoir is inferred based on the facies distribution maps.

Prestack density inversion using the Fatti equation constrained by the P- and S-wave impedance and density

Simultaneous prestack inversion is based on the modified Fatti equation and uses the ratio of the P- and S-wave velocity as constraints. We use the relation of P-wave impedance and density (PID) and S-wave impedance and density (SID) to replace the constant Vp/Vs constraint, and we propose the improved constrained Fatti equation to overcome the effect of P-wave impedance on density. We compare the sensitivity of both methods using numerical simulations and conclude that the density inversion sensitivity improves when using the proposed method. In addition, the random conjugate-gradient method is used in the inversion because it is fast and produces global solutions. The use of synthetic and field data suggests that the proposed inversion method is effective in conventional and nonconventional lithologies.

Target-oriented linear least squares and nonlinear, trust-region Newton inversions of plane waves using AVA and PVA data for elastic model parameters

Variations in elastic properties directly impact observed seismic amplitude and phase, as a function of incident angle (amplitude variation with angle [AVA] and with phase [PVA]). Conventional simultaneous prestack inversion uses precritical PP reflections, or joint PP and PS reflections, data to invert for elastic properties via linearized least-squares (LS) methods. Incorporating measured phase information as additional constraints for joint PP-PS and joint AVA-PVA inversions helps to stabilize the convergence path and improves the accuracy of the inverted parameters. Combining these dual joint constraints in a nonlinear trust-region reflective Newton (TRN) solver produces a robust inversion with improved convergence rates. Partial derivatives for the Jacobian and Hessian matrices are computed numerically. Two weighting functions, one for PP/PS and one for AVA/PVA data, are developed for minimizing the global objective function during inversion. Numerical results for data from a salt interface reflection in the SMAART JV Pluto model reveals a marked improvement in convergence when using the weighted nonlinear TRN method compared with a traditional linearized LS method, for clean and noisy data.

Pre-stack Simultaneous AVO Inversion and Lithology Prediction of Shale Gas Reservoir

Pre-stack Simultaneous AVO Inversion and Lithology Prediction of Shale Gas Reservoir

Sea Lion Field, North Falkland Basin: seismic inversion and quantitative interpretation

Extensive use has been made of seismic-derived quantitative interpretation for mapping and predicting reservoir properties in the Sea Lion Field, North Falkland Basin. The Sea Lion sands are acoustically hard compared to the encasing shales, with fairly constant rock properties. The fans are typically 20–60 m in thickness and are predominantly seismically tuned events. Detection of hydrocarbon fluid effects from seismic data has proved elusive to date. Extended elastic impedance (EEI) was selected as the appropriate seismic analysis tool. Almost all sands are visible on the full-stack seismic data. Coloured inversion of an EEI volume with a rotation angle ( χ ) of −70° (henceforth shown as EEI(−70)) was found to be an optimal sand predictor and is primarily sensitive to the shale volume of the sands. This EEI χ angle also allows detection of sand that is not observed on the full-stack seismic. The EEI(−70) coloured inversion data were also used to estimate net sand thickness and the net-to-gross maps of the fans. Subsequently, a new algorithm termed DT-AMP was used to apply seismic amplitude detuning to the full three-dimensional (3D) seismic volume. This has proved useful in the evaluation of new exploration targets beyond the Sea Lion Field area. A sand classification was performed using multiple EEI attributes, including lithology and fluid cubes. This indicates that there are differences in the amplitude v. offset (AVO) response across the main Sea Lion fan complex. Pre-stack simultaneous inversion was also performed using both deterministic and stochastic schemes. A three-term inversion was tested but density estimation was considered to be unreliable. Seismic data were tested at several stages to constrain the static reservoir model, using coloured, deterministic and stochastic inversion methods. The final static model incorporated a set of scenarios using net-to-gross maps inferred from the quantitative analysis of the EEI(−70) data.

Geophysical Evaluation Technology for Shale Gas Reservoir: A Case Study in Silurian of Changning Area in Sichuan Basin

Shale gas belongs to unconventional natural gas; it has many reservoir evaluation parameters hard to evaluate. Accurate calculation of parameters and comprehensive evaluation of favorable blocks are critical for geological evaluation, well deployment and reservoir reconstruction of shale gas. After research of Silurian Longmaxi Formation in Changning area in Sichuan Basin a petro physics model for shale gas reservoir is established through a large number of core data analysis and a calculation method for reservoir critical parameters is established through logging data. Based on logging results, the sensitivity analysis indicates that Vp/Vs is the most optimally sensitive parameter for shale gas reservoir identification and evaluation. The thickness, the total organic carbon content, the total gas content and the brittleness index of shale gas reservoir are realized by pre-stack simultaneous inversion technology. The reservoir classification standard is established, then the comprehensive evaluation for shale gas is achieved. There is a high consistency between evaluation results and actual drilling results, so the geophysical evaluation technology for shale gas reservoir can effectively guide well deployment and horizontal well drilling design and can provide technical support for efficient development of shale gas.

동해 울릉분지 CO<sub>2</sub> 저장소 특성 분석을 위한 탄성파 자료처리 및 역산

<TEX>$CO_2$</TEX> 지중저장은 국가 온실가스 감축 목표 달성에 가장 큰 역할을 담당할 것으로 평가되고 있으나, 포집분야 일부 기술을 제외하고 저장 및 실증에 대한 국내 연구는 여전히 부족한 실정이다. CCS(Carbon Capture and Storage)의 가장 큰 목표는 지하 퇴적 암반층에 <TEX>$CO_2$</TEX>를 안전하게 저장하는 것이며, 이를 위해서는 저장소의 저장용량 및 안정성등과 같은 지중저장 대상지층의 특성을 정확하게 파악하고 그에 맞는 주입 전략을 수립하여야 한다. 이번 연구에서는 한국석유공사가 2012년에 울릉분지에서 취득한 탄성파 탐사자료를 활용하여 <TEX>$CO_2$</TEX> 저장 후보 지층에 대한 탄성파 임피던스 역산을 수행하고, 공극률의 분포와 지층의 속성을 도출하여 <TEX>$CO_2$</TEX> 지중저장 가능성을 검토하였다. 우선, 탄성파 자료 역산의 신뢰도를 높이기 위해 다양한 방법의 잡음제거 기법을 적용하였고, 특히 본 자료의 주파수 및 위상 특성을 그대로 유지한 채 다중반사파를 제거할 수 있는 SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination), Radon Demultiple 기술을 활용하였다. 자료 역산을 위해 3개의 시추공에 대한 물리검층 자료를 분석하였는데, 탄성파 자료와의 상관도가 각각 0.648, 0.574, 0.342로 나타났으며 이는 초기 역산 모델 설정을 위한 저주파수 모델 생성에 활용하였다. 중합 전 역산을 통해 P-임피던스, S-임피던스 및 Vp/Vs 비 값을 도출하였으며, 이와 물리검층 결과의 비교, 분석을 통해 공극률 분포 양상을 확인함으로써 지중저장에 적합한 지층을 파악할 수 있었다. 향후 <TEX>$CO_2$</TEX> 주입 실증을 위해서는 지층에 대한 보다 세밀한 특성 분석과 모사를 통한 주입 이후 <TEX>$CO_2$</TEX> 거동예측이 필요할 것이다. <TEX>$CO_2$</TEX> geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing <TEX>$CO_2$</TEX> safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of <TEX>$CO_2$</TEX> storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the <TEX>$CO_2$</TEX> sequestration initiative. More detailed characterization of the geological storage and the simulation of <TEX>$CO_2$</TEX> migration might be an essential for the CCS demonstration.

Improving the quality of prestack inversion by prestack data conditioning

Prestack seismic inversion techniques provide valuable information of rock properties, lithology, and fluid content for reservoir characterization. The confidence of inverted results increases with increasing incident angle of seismic gathers. The most accurate result of simultaneous prestack inversion of P-wave seismic data is P-impedance. S-impedance estimation becomes reliable with incident angles approaching 30°, whereas density evaluation becomes reliable with incident angles approaching 45°. As the offset increases, we often encounter “hockey sticks” and severe stretch at large offsets. Hockey sticks and stretch not only lower the seismic resolution but also hinder long offset prestack seismic inversion analysis. The inverted results are also affected by the random noises present in the prestack gathers. We developed a three-step workflow to perform data conditioning prior to simultaneous prestack inversion. First, we mitigated the hockey sticks by using an automatic nonhyperbolic velocity analysis. Then, we minimized the stretch at the far offset by using an antistretch workflow. Last, we improved the signal-to-noise ratio by applying prestack structure-oriented filtering. We evaluated our workflow by applying it to a prestack seismic volume acquired over the Fort Worth Basin, Texas, USA. The results inverted from the conditioned prestack gathers have higher resolution and better correlation coefficients with well logs when compared to those inverted from conventional time-migrated gathers.