Partial Angle Stacks Research Articles

Reservoir characterization for hydrocarbon detection using Amplitude Variation with Angles constrained by localized rock physics template

Seismic data are prone to ambiguities because different scenarios of geological structures and rock properties can produce similar seismic reflections. The poorly compacted sandstone reservoirs of the ‘Jay’ Field produced seismic amplitude anomalies which may not be diagnostic of hydrocarbon presence. In this study, the different seismic amplitude reflections from ‘Jay’ Field reservoirs were investigated to determine the effect of fluids and lithologies on the observed seismic amplitudes for possible hydrocarbon identification away from well location. Amplitude Variation with Angles (AVA) and Rock physics techniques were used to analyze amplitude responses from sandstone reservoirs. These seismic amplitudes were extracted from the near and far partial angle stacks to identify changes in amplitudes with angles. Reservoir properties were examined to determine their influence on seismic responses through Rock Property Template (RPT) analysis. Well logs revealed that three of the seven identified reservoirs (Sands A, B and C) are brine saturated, Sand D is oil while Sands E, F and G are gas bearing. The reservoirs stratification is mainly the juxtaposition of low impedance sandstone and high impedance shale, such that P-velocity and density significantly influence impedance contrast in sandstone reservoirs and shale lithologies respectively. Changes in seismic amplitudes from near to far angles around Well location show that the gas reservoirs produce different AVOs that correspond to Classes II, III and IV respectively. The established Well log RPT supports AVA results of gas presence in the identified area away from Well location. This helps to reduce the risk associated with seismic amplitude ambiguities and enhanced certainty of gas presence at the location away from Well log information. In similar geological scenario, this work can serve as a useful guide to gas sand detection from seismic data.

Prediction of Gamma Ray data from pre-stack seismic reflection partial angle stacks using Continuous Wavelet Transform and convolutional neural network approach

Seismic inversion is one of the critical issues for geophysicists in the oil and gas industry. It is commonly used to estimate the distribution of facies-types and fluids in reservoirs across the value chain from exploration to development. However, the low vertical and spatial resolution of seismic data leads to large uncertainties in these estimations, which makes direct use of inversion results challenging. The objective of this study was the estimation of a 3D volume of Gamma Ray data from pre-stack seismic reflectivity partial angle stacks based on the Convolutional Neural Network architecture by representing data through the Continuous Wavelet Transform. The proposed methodology used 132 deviated wells from the Azeri and Chirag parts of the Azeri – Chirag – Gunashli field in the South Caspian Basin as training data. Blind tests show promising Gamma Ray predictions. To optimize the predictions, sensitivity analysis was performed on the Continuous Wavelet Transform parameters (wavelet types, range of pseudo-frequencies, etc.), the Convolutional Neural Network architecture (number of convolutional and pooling layers, dropout, activation functions) and the network parameters (batch size, number of epochs, optimizers, etc.). Due to the vast amount of data required to speed up the learning process, simulations were performed on a Graphics Processing Unit based on the Compute Unified Device Architecture platform.

Hydrocarbon reservoir delineation using simultaneous and elastic impedance inversions in a Niger Delta field

The global energy demand is increasing while production from mature fields is drastically reducing consequently, oil and gas industries are expanding activities into more challenging areas. The inability of the traditional seismic data to properly delineate hydrocarbon reservoirs from subtle seismic features in ‘Sandfish’ field located offshore, Niger Delta informed the use of simultaneous and elastic impedance inversion. The elastic and derived volumes from seismic inversion would reduce risk, enhance hydrocarbon discovery and optimize development plans in the study area. Four ‘Sandfish’ (Sfn) wells (Sfn-01, Sfn-02, Sfn-04 and Sfn-05), check-shots and 3D seismic data of five angle stacks (6–12°, 12–18°, 18–26°, 26–32° and 32–42°) were used in the study. Low frequency (0–2 Hz) models were generated from interpolation of high-cut-filtered compressional wave velocity log (P-sonic), shear wave velocity log (S-sonic) and density log guided by interpreted four seismic horizons. The low frequency models broaden the spectrum of the elastic volumes and also served as inversion constraints. The five partial angle stacks varying from 6–42° were simultaneously inverted using Jason’s Rock-Trace® inversion software which iterated trial inversions until the model sufficiently matched the seismic data. The near (6–12°) angle and far-far (32–42°) angle stacks were also inverted and compared with the inverted volumes from the simultaneous inversion. This was carried out to determine the effectiveness of near and far-far elastic impedance volume in delineating hydrocarbon reservoirs. The inverted elastic volumes P-impedance (ZP), S-impedance (ZS), density (ρ), near and far-far elastic and derived volumes lambda-rho (λρ), mu-rho (µρ), Poisson’s-ratio (σ) reveal vertical and lateral continuity of the reservoirs identified (K01, N01 and P01) at 2179 m, 2484 m and 3048 m, respectively. The delineated reservoirs showed good match with the sand tops away from the well control validated by a blind well test. The cross-plot of inverted ZP from simultaneous inversion and well ZP gave correlation coefficient of 86% indicative of high quality inverted volume which will reduce exploration risk. The plot of inverted ZP from simultaneous inversion and inverted far-far elastic volume reflected 82% correlation coefficient indicating that this method could be adopted in other fields with limited data and similar geological setting. Hence, the study has shown the efficacy of elastic volumes in delineating hydrocarbon reservoirs which can help locate optimum region for development wells.

Seismic-to-well tie of a field of the Nigerian Delta

This paper presents a rigorous but pragmatic and data driven approach to the science of making seismic-to-well ties. This pragmatic approach is consistent with the interpreter’s desire to correlate geology to seismic information by the use of the convolution model, together with least squares matching techniques and statistical measures of fit and accuracy to match the seismic data to the well data. Three wells available on the field provided a chance to estimate the wavelet (both in terms of shape and timing) directly from the seismic and also to ascertain the level of confidence that should be placed in the wavelet. The reflections were interpreted clearly as hard sand at H1000 and soft sand at H4000. A synthetic seismogram was constructed and matched to a real seismic trace and features from the well are correlated to the seismic data. The prime concept in constructing the synthetic is the convolution model, which represents a seismic reflection signal as a sequence of interfering reflection pulses of different amplitudes and polarity but all of the same shape. This pulse shape is the seismic wavelet which is formally, the reflection waveform returned by an isolated reflector of unit strength at the target depth. The wavelets are near zero phase. The goal and the idea behind these seismic-to-well ties was to obtain information on the sediments, calibration of seismic processing parameters, correlation of formation tops and seismic reflectors, and the derivation of a wavelet for seismic inversion among others. Three seismic-to-well ties were done using three partial angle stacks and basically two formation tops were correlated.
 Keywords: seismic, well logs, tie, synthetics, angle stacks, correlation,

Application of spectral decomposition as a direct hydrocarbon indicator within the challenging rock physics environment

A study was conducted to use low-frequency amplitudes obtained through spectral decomposition as a direct hydrocarbon indicator within the geologically and seismically challenging area. An offshore data set from the Gulf of Thailand with well-known geology and good well control for both water and hydrocarbon bearing zones were used in this study. The rocks physics reveals similar P-impedance for gas and water-wet sands. Moreover, organic shales have similar Poisson’s ratio as of gas saturated zones. This makes differentiation of fluids and lithologies through post-stack seismic inversion and AVO analysis difficult. Reservoir wedge modelling, spectral decomposition of the synthetic and field data and analyses were conducted to understand the spectral decomposition response to thickness variation and reservoir fluids. Spectral decomposition was also applied on partial angle stacks (near, mid and far). Gas sands show bright amplitudes at low frequencies (from 10 to 15 Hz). However, spectral decomposition of the synthetic seismogram of the organic shales indicates that it consists of only relatively higher frequencies (greater than 25 Hz). Therefore, low-frequency amplitudes of spectral decomposition may help to identify hydrocarbon saturated zones.

Seismic imaging of the Solfatara crater (Campi Flegrei caldera, southern Italy): New evidence of the fluids migration pathways in the shallow structures

Seismic imaging is used in this work, to reconstruct the shallow structure of the Solfatara crater, a surface marker of deep magmatic activity inside Campi Flegrei caldera (Southern Italy). We analyze the 1D orthogonal seismic arrays deployed in NNE-SSW directions for 400 m through the Solfatara crater during the recent active experiment RICEN (Repeated Induced Earthquake and Noise) performed in the framework of the EU project MEDSUV. Seismic data have been edited in the pre-stack stage by removing the noisy traces, low-frequency noise, and reduce the ground roll phases. Then, a velocity analysis has been carried out starting from the velocity spectrum to obtain a RMS velocity model, which has been followed by NMO, residual statics, and DMO corrections. We used the post-stack Kirchhoff migration technique before the extraction of the energy, root mean square, envelope and sweetness attributes defining the highest amplitude zones, the time-gain attribute in order to interpret the deep reflectors and the variance attribute to define the faults, discontinuities, and chaotic zones. Amplitude Versus Offset (AVO) analysis has been performed to identify the gas-saturated zone using partial angle-stacks, which is a benchmark to verify the presence of gas. The main contribution of this work is to provide a more detailed and improved seismic reflection image of the shallow depth of the Solfatara crater. The reliability of our velocity model has been assessed through the use of the Vp velocity model previously obtained by the non-linear Bayesian technique. This provides a final stack showing that the shallower minor faults and the extension of the major faults represent the main pathways for the uprising fluids. We present the visual evidence for the fluids trapped in the shallower part of the crater at depths between 20 and 50 m below the surface of the crater.

Frequency bandwidth enhancement using continuous wavelet transform and random noise attenuation by f-xy filtering technique – a case study from Badin oilfield, Indus basin, Pakistan

Routine seismic data processing does not always meet the quantitative interpreters’ expectations especially in areas like Badin, where prospective thin bed B – sand interval is ambiguous throughout the seismic volume. Continuous Wavelet Transform (CWT) provides detailed description of seismic signal in both time and frequency without compromising on window length and a fixed time-frequency resolution over time-frequency spectrum. We present enhancement of seismic data for effective interpretation using the bandwidth extension technique. Implementing bandwidth extension, the dominant frequency increases from 18 Hz to 30 Hz and the frequency content boosted from 40 Hz to 60 Hz. Noise inclusion by the technique was suppressed by F-XY predictive filter and F-XY deconvolution with edge preserve smoothing. Phase and spectral balancing were applied to partial angle stacks to stabilize the phase rotation across the 3D survey, particularly for far offset stack. Frequency was balanced using surface consistent spectrum balancing, and subjected to trace scaling for amplitudes balance and preservation. Results of the techniques yielded unique improvement on the data resolution and subtle information about the thin sand beds were better delineated. Tuning thickness analysis reveals the usefulness of bandwidth extension, with an increase of 30% in the resolving power of thin beds.

AVO inversion on unconventional reservoirs: systematic estimation of uncertainty in the Vaca Muerta shale

Abstract Amplitude versus offset inversion is widely used in reservoir characterization, but its implementation on unconventional reservoirs represents a challenge owing to the subtle changes of elastic parameters that demarcate profitable areas. For this reason, it is important to have an estimation of the uncertainty expected from seismic inversion to improve the interpretation of inverted results. We have implemented a systematic estimation of uncertainty of relative elastic properties obtained by damped least squares inversion of Aki and Richards and Fatti et al. approximations of Zoeppritz’s equation. Well log data of the Vaca Muerta unconventional shale in Argentina was used to generate synthetic angle gathers, varying in terms of asignal-to-noise ratio, range of angle coverage and number of partial angle stacks. The inversion results provide a systematic estimation of the uncertainty of the inverted coefficients. Results show that signal-to-noise ratio and range of angle coverage of the seismic data are key parameters to assess the feasibility of the inversion. In case of characterization based on acoustic impedance, the inverted parameters show good correlation with the model, with these correlation values being predicted by the parameter resolution matrix values.

Blocky inversion of multichannel elastic impedance for elastic parameters

Petrophysical description of reservoirs requires proper knowledge of elastic parameters like P- and S-wave velocities (Vp and Vs) and density (ρ), which can be retrieved from pre-stack seismic data using the concept of elastic impedance (EI). We propose an inversion algorithm which recovers elastic parameters from pre-stack seismic data in two sequential steps. In the first step, using the multichannel blind seismic inversion method (exploited recently for recovering acoustic impedance from post-stack seismic data), high-resolution blocky EI models are obtained directly from partial angle-stacks. Using an efficient total-variation (TV) regularization, each angle-stack is inverted independently in a multichannel form without prior knowledge of the corresponding wavelet. The second step involves inversion of the resulting EI models for elastic parameters. Mathematically, under some assumptions, the EI's are linearly described by the elastic parameters in the logarithm domain. Thus a linear weighted least squares inversion is employed to perform this step. Accuracy of the concept of elastic impedance in predicting reflection coefficients at low and high angles of incidence is compared with that of exact Zoeppritz elastic impedance and the role of low frequency content in the problem is discussed. The performance of the proposed inversion method is tested using synthetic 2D data sets obtained from the Marmousi model and also 2D field data sets. The results confirm the efficiency and accuracy of the proposed method for inversion of pre-stack seismic data.

Lithology and fluid prediction from simultaneous seismic inversion over Sandfish field, Niger Delta, Nigeria

Seismic inversion has been widely practiced in the oil and gas industry because it generates broad bandwidth of impedance data which maximizes vertical resolution and minimizes tuning effects. The lack of accurate prediction of lithology and fluid content of subtle features identified in seismic data acquired over the Sandfish field, Niger Delta, Nigeria necessitated the use of seismic inversion. In this paper, simultaneous seismic inversion is adopted to integrate seismic and well data for quantitative interpretation and uncertainty assessment of the subsurface reservoirs in the Sandfish field. Three Sandfish (Sfn) wells with the required petrophysical logs, check-shot data, high quality 3D seismic data of five angle stacks (6–12°, 12–18°, 18–26°, 26–32°, and 32–42°) were used for the analysis. A feasibility study including cross-plots of petrophysical and elastic properties from well data was first carried out to establish rock property relationships in the interval of interest. Biot-Gassmann fluid substitution analysis was also used to reveal sensitivity of rock properties to pore-fill type. Low frequency (0–2 Hz) models were generated from interpolation of high-cut-filtered P-sonic, S-sonic, and density logs guided by interpreted seismic horizons. The low frequency models were used to broaden the spectrum to estimate elastic volumes. The five partial angle stacks were simultaneously inverted using Jason’s Rock-Trace® inversion software which iterated trial inversions until the model sufficiently matched the seismic data. The inverted P-impedance (ZP), Simpedance (ZS), and density (ρ) were used to derive Poisson’s ratio (σ), volume of sand (Vsand), lambda-rho (λρ), and mu-rho (µρ). The cross-plot of λρ with µρ from well data looks similar to that from inverted results. Sands and shales are discriminated on the basis of sands having low values of µρ. Hydrocarbon-bearing sands are differentiated from water-bearing sands and shales on the basis of having lowest values of λρ. The Biot-Gassmann fluid substitution analysis at reservoir N-01 reveals typical class III amplitude variation with angle (AVA) responses for low-impedance hydrocarbon sands. The lithology and fluid prediction maps extracted from Vsand and σ at the N-01 seismic horizon show variation in lithology and fluid types for the entire volume. The inversion products reveal heterogeneities in the reservoirs away from well control validated by a blind well test. Hence, the study shows that rock-property model from a simultaneous inversion is an effective predictive tool for lithology and fluid types which in turn can guide well placement and predict reservoir development in the field of study.

Constraints on melt content of off‐axis magma lenses at the East Pacific Rise from analysis of 3‐D seismic amplitude variation with angle of incidence

AbstractWe use 3‐D multichannel seismic data to form partial angle P wave stacks and apply amplitude variation with angle (AVA) crossplotting to assess melt content and melt distribution within two large midcrustal off‐axis magma lenses (OAMLs) found along the East Pacific Rise from 9°37.5′N to 9°57′N. The signal envelope of the partial angle stacks suggests that both OAMLs are partially molten with higher average melt content and more uniform melt distribution in the southern OAML than in the northern OAML. For AVA crossplotting, the OAMLs are subdivided into seven ~1 km2 analysis windows. The AVA crossplotting results indicate that the OAMLs contain a smaller amount of melt than the axial magma lens (AML). For both OAMLs, a higher melt fraction is detected within analysis windows located close to the ridge axis than within the most distant windows. The highest average melt concentration is interpreted for the central sections of the OAMLs. The overall low OAML melt content could be indicative of melt lost due to recent off‐axis eruptions, drainage to the AML, or limited mantle melt supply. Based on the results of this and earlier bathymetric, morphological, geochemical, and geophysical investigations, we propose that the melt‐poor OAML state is largely the result of limited melt supply from the underlying mantle source reservoir with smaller contribution attributed to melt leakage to the AML. We hypothesize that the investigated OAMLs have a longer period of melt replenishment, lower eruption recurrence rates, and lower eruption volumes than the AML, though some could be single intrusion events.

GAS SAND DETECTION USING ROCK PHYSICS AND PRE-STACK SEISMIC INVERSION, EXAMPLE FROM OFFSHORE NILE DELTA, EGYPT

Well logs and three-dimensional (3-D) partial angle stacks and full angle stack seismic volumes are used inthis study with the purpose of detecting gas sands using rock physics and pre-stack inversion workflows.Integration of pre-stack inversion and rock physics analysis can improve the characterization of the latePliocene gas sandstone reservoir, offshore Nile Delta. The inversion was performed using a deterministicwavelet set. Rock physics was used to enhance the VP, VS, and density volumes from the inversion. The presentstudy performed in three phases: AVO analysis, pre-stack inversion, and lambda-mu-rho (LMR) analysis. Theresults from the different crossplots, such as P-Impedance vs. Vp/Vs, show that the gas sands are clearlyseparated from brine sands and shale. By maximizing the potential offered from the elastic properties such asλρ, μρ and Vp/Vs ratio we were able to define the limits and cutoffs which sufficiently separate the gas sandbodies. The resulted volumes were used to better define the late Pliocene reservoir and optimize a new welllocation. The pre-stack inversion and AVO/rock physics studies resulted in a new Gas Initial In Place (GIIP)calculation that was doubled in the P50 case from the original estimation based only on the seismic amplitudedata. The chance of success was increased and a new well is proposed to drain the gas in the eastern flank ofChannel 1.

Joint Impedance and Facies Inversion – Seismic inversion redefined

In this paper we will first review the industry-standard simultaneous inversion method (which derives continuous impedances) and subsequently identify some pitfalls. We will then introduce our new Joint Impedance and Facies Inversion technology (which we call Ji-Fi for short in this paper), which overcomes these pitfalls by recasting the seismic inverse problem as mixed discrete/continuous. Having so captured the correct physics, we apply this first on a wedge model, followed by a case study, before drawing some conclusions. Note that in this paper, it is assumed that the seismic to be inverted is an ensemble of true amplitude partial angle stacks with corresponding wavelets derived from well ties.

AVO inversion and Lateral prediction of reservoir properties of Amangi hydrocarbon field of the Niger Delta area of Nigeria

Well log modelling was performed using a complete suite of compressional, shear and density logs to understand and determine the expected angle dependent effects in the seismic reflection data and also to estimate wavelets for the different input stacks. The available well controls were used in wavelet estimation and we incorporated AVO modelling to properly account for AVO effects. We partitioned the 3D seismic reflection data into three partial angle stacks of near (0 o - 10 o ), mid (11 o - 20 o ) and far (21 o - 30 o ). Wavelets were estimated separately for each angle stack to enable the inversion to compensate for offset dependent phase, bandwidth, tuning and normal moveout (NMO) stretch effects which could affect the amplitude and phase spectra of the data. We then simultaneously inverted multiple angle stacks to transform P-wave offset seismic reflection data to P-impedance and S-impedance volumes. These impedance volumes were interpreted separately. This method supported interpretation in this field where the reservoirs' sandstones and shales cannot be distinguished from the P- impedance alone.

Multidimensional scaling for the evaluation of a geostatistical seismic elastic inversion methodology

Due to the nature of seismic inversion problems, there are multiple possible solutions that can equally fit the observed seismic data while diverging from the real subsurface model. Consequently, it is important to assess how inverse-impedance models are converging toward the real subsurface model. For this purpose, we evaluated a new methodology to combine the multidimensional scaling (MDS) technique with an iterative geostatistical elastic seismic inversion algorithm. The geostatistical inversion algorithm inverted partial angle stacks directly for acoustic and elastic impedance (AI and EI) models. It was based on a genetic algorithm in which the model perturbation at each iteration was performed recurring to stochastic sequential simulation. To assess the reliability and convergence of the inverted models at each step, the simulated models can be projected in a metric space computed by MDS. This projection allowed distinguishing similar from variable models and assessing the convergence of inverted models toward the real impedance ones. The geostatistical inversion results of a synthetic data set, in which the real AI and EI models are known, were plotted in this metric space along with the known impedance models. We applied the same principle to a real data set using a cross-validation technique. These examples revealed that the MDS is a valuable tool to evaluate the convergence of the inverse methodology and the impedance model variability among each iteration of the inversion process. Particularly for the geostatistical inversion algorithm we evaluated, it retrieves reliable impedance models while still producing a set of simulated models with considerable variability.

Integration of geology, rock physics, logs, and prestack seismic data for reservoir porosity estimation

The main objective of this article is to obtain reservoir properties, such as porosity, both at the well locations and in the interwell regions from seismic data and well logs. The seismic and well-log data sets are from an oil field in eastern Saudi Arabia, and the main target is a Jurassic carbonate reservoir. The geology of carbonate reservoirs in Saudi Arabia is well understood. Reservoir porosity estimation is essential and needs to be determined for flow simulation and reservoir management. A major component of this study is establishing the relation between the P-impedance and porosity using well-log data. An amplitude-versus-angle seismic inversion algorithm was used to invert the three-dimensional impedance volumes (i.e., P-impedance and S-impedance) given partial angle stacks of seismic traces representing reflection amplitude variations with angle of incidence. These impedance volumes were used to estimate porosity between the well locations. The seismic and log data provided a-priori information (i.e., the initial starting model and source wavelet estimate) necessary for obtaining geologically consistent results.

Detection and Spatial Delineation of Thin-Sand Sedimentary Sequences With Joint Stochastic Inversion of Well Logs and 3D Prestack Seismic Amplitude Data

Summary We describe the successful application of a new prestack stochastic inversion algorithm to the spatial delineation of thin reservoir units otherwise poorly defined with deterministic inversion procedures. The inversion algorithm effectively combines the high vertical resolution of wireline logs with the relatively dense horizontal coverage of 3D prestack seismic amplitude data. Multiple partial-angle stacks of seismic amplitude data provide the degrees of freedom necessary to estimate spatial distributions of lithotype and compressional-wave (P-wave) and shear-wave (S-wave) velocities in a high-resolution stratigraphic/sedimentary grid. In turn, the estimated volumes of P- and S-wave velocity permit the statistical cosimulation of lithotype-dependent spatial distributions of porosity and permeability. The new stochastic inversion algorithm maximizes a Bayesian selection criterion to populate values of lithotype and P- and S-wave velocities in the 3D simulation grid between wells. Property values are accepted by the Bayesian selection criterion only when they increase the statistical correlation between the simulated and recorded seismic amplitudes of all partial-angle stacks. Furthermore, inversion results are conditioned by the predefined measures of spatial correlation (variograms) of the unknown properties, their statistical cross correlation, and the assumed global lithotype proportions. Using field data acquired in a fluvial-deltaic sedimentary-rock sequence, we show that deterministic prestack seismic-inversion techniques fail to delineate thin reservoir units (10-15 m) penetrated by wells because of insufficient vertical resolution and low contrast of elastic properties. By comparison, the new stochastic inversion yields spatial distributions of lithotype and elastic properties with a vertical resolution between 10-15 m that accurately describe spatial trends of clinoform sedimentary sequences and their associated reservoir units. Blind-well tests and cross validation of inversion results confirm the reliability of the estimated distributions of lithotype and P- and S-wave velocities. Inversion results provide new insight to the spatial and petrophysical character of existing flow units and enable the efficient planning of primary and secondary hydrocarbon recovery operations.

Sensitivity analysis of data-related factors controlling AVA simultaneous inversion of partially stacked seismic amplitude data: Application to deepwater hydrocarbon reservoirs in the central Gulf of Mexico

We consider the inversion of synthetic and recorded seismic amplitude variation with angle AVA data to appraise the influence of several data-related factors that control the vertical resolution and accuracy of the estimated spatial distributions of elastic properties. We use measurements acquired in deepwater hydrocarbon reservoirs in the central Gulf of Mexico to generate synthetic seismic amplitude data and evaluate inversion results with both synthetic and recorded seismic amplitudes. Detailed sensitivity analysis of synthetic amplitude data indicates that, even in the most ideal scenario (perfectly migrated data, isotropic media, noise-free seismic amplitude data, sufficient far-angle coverage, and accurate estimates of angle-dependent wavelets and low-frequency components), input elastic models are not reconstructedaccurately by the inversion of synthetic seismic amplitudes. We attribute this result to the relatively low vertical resolution of the seismic amplitude data. P-wave impedance is the most accurate of the inverted properties, followed by S-impedance and bulk density. Additionally, sufficient far-angle coverage is crucial for the accurate estimation of 1D distributions of S-impedance and bulk density. We show that time alignment of partial-angle stacks for correcting residual NMO effects improves the vertical resolution of the estimated spatial distributions of elastic parameters and consistently decreases the data misfit. Finally, we found that the accuracy of the inverted distributions of elastic parameters is improved substantially by (1) increasing the preserved AVA information via multiple single-angle stacks, (2) correcting the P-wave velocity field used for calculating angles in partial-angle stacking, and (3) excluding far-angle data with low signal-to-noise ratios.

Reservoir characterisation of the Flag Sandstone, Barrow Sub-basin, using an integrated, multi-parameter seismic AVO inversion technique

The Early Cretaceous Flag Sandstone within the Barrow Sub-basin is a proven hydrocarbon reservoir. The main trapping mechanism is four-way dip closed anticlines, formed by drape compaction. An integrated, multi-parameter seismic AVO inversion technique was utilized that improved the mapping of the Flag Sandstone and identified the presence of trapped hydrocarbons. The identification of the Flag Sandstone on seismic sections is complicated due to a low acoustic impedance contrast between the Flag Sandstone and the overlying shales. The same interface gives a good AVO response. Previous interpretation efforts have used the seismic AVO response to map the top of the Flag Sandstone on far-angle stacks. These efforts were very successful for mapping structure but were influenced by wavelet tuning effects and were limited for high-grading the structures based on hydrocarbon potential. To aid in characterizing the fluid distribution in the reservoir rocks a simultaneous AVO inversion algorithm was used based on three partial angle stacks and conditioned well logs, inverting for acoustic and shear impedance. The results of this multi-parameter impedance inversion produced a variety of attributes. The Vp/Vs attribute was aimed at improving the TWT structural pick whereas P-impedance became the basis for discriminating water and oil saturated sands.