Seismic Amplitude Versus Offset Research Articles

Frequency-dependent AVO inversion applied to physically based models for seismic attenuation

SUMMARYSeismic inversion of amplitude versus offset (AVO) data in viscoelastic media can potentially provide high-resolution subsurface models of seismic velocities and attenuation from offset/angle seismic gathers. P- and S-wave quality factors (Q), whose inverse represent a measure of attenuation, depend on reservoir rock and pore fluid properties, in particular, saturation, permeability, porosity, fluid viscosity and lithology; however, these quality factors are rarely taken into account in seismic AVO inversion. For this reason, in this work, we aim to integrate quality factors derived from physically based models in AVO inversion by proposing a gradient descent optimization-based inversion technique to predict the unknown model properties (P- and S-wave velocities, the related quality factors and density). The proposed inversion minimizes the non-linear least-squares misfit with the observed data. The optimal solution is iteratively obtained by optimizing the data misfit using a second-order limited-memory quasi-Newton technique. The forward model is performed in the frequency–frequency-angle domain based on a convolution of broad-band signals and a linearized viscoelastic frequency-dependent AVO (FAVO) equation. The optimization includes the adjoint-state-based gradients with the Lagrangian formulation to improve the efficiency of the non-linear seismic FAVO inversion process. The inversion is tested on synthetic seismic data, in 1-D and 2-D, with and without noise. The sensitivity for seismic quality factors is evaluated using various rock physics models for seismic attenuation and quality factors. The results demonstrate that the proposed inversion method reliably retrieves the unknown elastic and an-elastic properties with good convergence and accuracy. The stability of the inverse solution especially seismic quality factors estimation relies on the noise level of the seismic data. We further investigate the uncertainty of the solution as a function of the variability of the initial models.

Bayesian Seismic AVO Inversion Using a Laterally Coupled Multimodal Prior Model

A Bayesian seismic amplitude versus offset (AVO) inversion scheme with a laterally coupled prior model for porosity, water saturation, and volume of clay is proposed. A 2-D section and a 3-D volume of an oil reservoir are studied. The oil reservoir is considered at the initial state, which entails gravitationally induced bimodality in the water saturations along vertical traces. A selection Gaussian random field (S-GRF) prior model, capable of representing this bimodality, is specified for porosity, water saturation, and volume of clay. The S-GRF is specified to have lateral correlation, which may reduce the impact of trace-unique signal errors in the seismic AVO data on the inversion results. The likelihood model is linear and Gaussian, for which the S-GRF prior model is conjugate; hence, the posterior model is also an S-GRF. The form of the posterior distribution is therefore known and its parameter values can be analytically computed. Real seismic AVO data from the 2-D section and the 3-D volume are inverted and the results appear to be reliable along validation wells and represent a geologically plausible reservoir design. Furthermore, a notable variance reduction in the laterally coupled posterior model relative to an alternative posterior model without lateral coupling is achieved.

Uncertainty Quantification in Classifying Complex Geological Facies Using Bayesian Deep Learning

Understanding geological differences in a proved reservoir requires precise facies classification. Predicting facies from seismic data is frequently seen as an inverse uncertainty quantification problem in seismic reservoir characterization. Typically, the uncertainty in the model parameters that regulate the geographic distributions is being ignored. The target facies and its uncertainty can be determined by calculating the posterior distribution of a Bayesian inverse problem conditioned by the seismic data, in which the model parameters are inferred from the observed seismic data using a Bayesian inference framework. It is believed that such facies classification model has a unique set of model parameters that best fits it. The proposed work is unique in that it quantifies the epistemic uncertainty of the predicted facies in blind well conditioned by Seismic Amplitude Versus Offset (AVO-Seismic) attributes in the Bayesian inference framework. Under this framework, parameter uncertainties of the neural net. weights and biases are calculated using their posterior distributions from the ensamble models generated by Marcov-Chains Monte-Carlo (MCMC) by assuming that the prior values of the weights and biases are uninformative. The proposed approach is also demonstrated on Synthetic Amplitude Versus Offset (AVO-Synthetic) dataset (derived from the well log information) and we have found high relevance in the predicted results. For comparision, a plain Deep Learning and Deep learning with Monte Carlo Dropout are employed and the results indicate that our model performs more efficiently comparing to the others indicating the possibility of the model to be used in real world solution to adequate facies classication.

Bayesian Inversion of Time-Lapse Seismic AVO Data for Multimodal Reservoir Properties

We consider time-lapse seismic amplitude versus offset (AVO) inversion for the reservoir properties porosity and water saturation, with a focus on monitoring the evolution of water saturation in a dynamic setting of ongoing production. We operate in a Bayesian framework based on the integration of seismic AVO modeling and rock physics relations. One major challenge in the inversion of seismic data for reservoir properties is the multimodality of these properties. Fluid saturation is generally bimodal due to the gravity effect, and often distinctly so, with abrupt spatial mode transitions. The novelty of the proposed approach is the assumption of a selection Gaussian random field (S-GRF) for the prior spatial model of porosity and water saturation, which can represent the multimodal characteristics of these reservoir properties. The likelihood model is Gauss-linear and based on linearized seismic and rock physics models, which entails that the associated posterior model is also an S-GRF, with analytically assessable parameters. Hence, the posterior model is capable of representing multimodality and abrupt spatial mode transitions. Two realistic case studies are considered; the production of an oil reservoir in the North Sea, and the injection of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> into a subsurface potential CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> storage unit. Focus is on the movement of the oil–water-contacts along a vertical profile in the first case, and on the expansion of the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> region in a cross section in the other, both of which can be inferred from the changes in the water saturations. The results are considered to be very encouraging and the proposed statistical formulation appears to be particularly well suited for fluid monitoring problems of the described type.

Identification of shallow gas by seismic data and AVO processing: Example from the southwestern continental shelf of the Ulleung Basin, East Sea, Korea

This study investigates the evidence of shallow gas from a newly collected dataset comprising 2D multi-channel seismic (MCS), single-channel seismic (SCS), Chirp sub-bottom profiler (SBP), and multi-beam echo sounder (MBES) data from the southwestern continental shelf of the Ulleung Basin, East Sea, Korea. Various indicators of shallow gas were identified in this part the shelf, including seismic chimneys, acoustic flares in the water column, pockmarks, enhanced reflections, and acoustic blanking. Seismic chimneys, which are related to fluid leakage within the subsurface, are characterized weak to high amplitude, upturned or concave-upward internal reflection with polarity reversal in MCS section, whereas they are faint or transparent on SCS section with 700 Hz and Chirp SBP sections with 3.5 kHz frequency. Acoustic flares, which are diagnostics of active gas venting, were detected only on the Chirp SBP sections. There is also evidence of small-scale depressions, immediately below the acoustic flares; these are interpreted as formed by the sudden explosion of gas. Enhanced reflections (~3 km-long) concordant with stratification are observed at different levels. Acoustic blanking anomalies, caused by absorption of acoustic energy due to the presence of gas, are seen in the range 50–200 ms TWT below seabed. Amplitude versus offset (AVO) analysis indicates the presence of free gas ca. 350 ms TWT below sea surface using the MCS dataset recorded by a 600 m-long streamer cable. The AVO cross-section shows that the lower repetitive signals in the MCS data are due to the gas plume, not lithological contrast. Our study highlights that AVO analysis is an extremely useful tool for identifying free gas, helping to discriminate water-gas contacts and bright events among the chaotic signals on the MCS data. • We identify shallow gas based on seismic data from SW shelf of Ulleung Basin. • Seismic chimneys, gas flares, enhanced reflections are most common. • We compare acoustic anomalies of shallow gas with different resolutions. • We verify the presence of gas by AVO analysis.

Combining CSEM or gravity inversion with seismic AVO inversion, with application to monitoring of large-scale CO2 injection

A sequential inversion methodology for combining geophysical data types of different resolutions is developed and applied to monitoring of large-scale CO2 injection. The methodology is a two-step approach within the Bayesian framework where lower resolution data are inverted first, and subsequently used in the generation of the prior model for inversion of the higher resolution data. For the application of CO2 monitoring, the first step is done with either controlled source electromagnetic (CSEM) or gravimetric data, while the second step is done with seismic amplitude-versus-offset (AVO) data. The Bayesian inverse problems are solved by sampling the posterior probability distributions using either the ensemble Kalman filter or ensemble smoother with multiple data assimilation. A model-based parameterization is used to represent the unknown geophysical parameters: electric conductivity, density, and seismic velocity. The parameterization is well suited for identification of CO2 plume location and variation of geophysical parameters within the regions corresponding to inside and outside of the plume. The inversion methodology is applied to a synthetic monitoring test case where geophysical data are made from fluid-flow simulation of large-scale CO2 sequestration in the Skade formation. The numerical experiments show that seismic AVO inversion results are improved with the sequential inversion methodology using prior information from either CSEM or gravimetric inversion.

Seismic evidence of free gas migration through the gas hydrate stability zone (GHSZ) and active methane seep in Krishna-Godavari offshore basin

Abstract Seismic amplitude versus offset (AVO) analysis was performed on the multichannel seismic data in the vicinity of Site NGHP-01-10, where thick fracture-filled gas hydrate is reported, to understand the fluid migration in fracture dominated gas hydrate system. Amplitude preserved common image gathers (CIG) are used in extracting the seismic amplitude with offset for seafloor, bottom simulating reflectors (BSR), and different horizons within the gas hydrate stability zone (GHSZ). The extracted amplitudes are fitted with three-term Shuey's AVO approximation to estimate the intercept and gradient values. Based on the intercept and gradient values, two distinct classes of seismic AVO responses are observed; class IV AVO (decreasing negative amplitudes with increasing offsets) and class III AVO (increasing negative amplitudes with increasing offsets) for the BSR and other horizons above the BSR. The large negative intercept and gradient values which indicate class III AVO ranges from −0.2 to −1.8 for the inline seismic profile and from −0.01 to −0.3 for the crossline profile. The presence of class III AVO anomaly within the gas hydrate stability zone (GHSZ) provides evidence of existence of free gas which may be migrating along the fault system. Some of the active faults are exposed on the surface and show gas venting signatures such as gas-flares and pockmarks in the multibeam data.

Prospects delineation and evaluation using the CDP gathers characterization, onshore Nile Delta, Egypt

In the last decade, the seismic AVO analysis have become prominent in the direct hydrocarbons indicator (DHI), aimed at characterizing the fluid content or the lithology of a possible reservoir and reducing the exploration drilling risk. This research discuss the impact of studying the common depth point (CDP) gathers on Near, Mid and Far-offsets, to verify the credibility of the amplitude response in the prospect evaluation, through analyzing a case study of two exploratory wells; one has already penetrated a gas-bearing sandstone as a reservoir and the other one is dry-sand, but drilled in two different prospects, using the amplitude versus offset (AVO) analysis, to understand the reservoir configuration and its relation to the different amplitude response. The results show, that the missing of the short-offset data is the reason of the false anomaly encountered in the dry sand, due to some urban surface obstacles during acquiring the seismic data in the field especially, the study area is located in El Mansoura city, which it is a highly cultivated flat terrain, with multiple channels and many large orchards on the edge of the river, and sugar cane and rice fields. Several lessons have been learned, which how to differentiate between the gas reservoirs and non-reservoirs, by understanding the relation between the Near and Far-offset traces, to reduce the amplitude anomalies to their right justification, where missing of Near-offset data led to a pseudo-amplitude anomaly. The results led to a high success of exploration ratio as the positives vastly outweigh the negatives.

Uncovering Seismic HTI Anisotropy of the Cooper Basin

3D seismic data from the Cooper Basin exhibit horizontal transverse isotropy (HTI) anisotropy in amplitude versus offset (AVO) and interval migration velocity. Theoretically, vertical fractures and in-situ stress can induce HTI anisotropy. The main objective is to determine if the HTI anisotropy is caused by fractures or by the Cooper Basin’s large difference between minimum and maximum horizontal stress. We compare migration velocity anisotropy and seismic AVO anisotropy extracted from a high-quality 3D survey with a “ground truth” of dipole sonic logs, borehole breakout, and fractures interpreted from image logs. The AVO anisotropy is inverted using Ruger AVO algorithm and Fourier Coefficient algorithm that give similar results. Fractures interpreted from image logs are primarily oriented approximately 30° from SH. Our work suggests that stress is the dominant cause of the HTI anisotropy observed in the seismic data. The fact that seismic anisotropy is parallel with current SH and not aligned with the observed fractures suggests that Cooper Basin large differential stress causes the anisotropy observed on seismic.

Seismic processing, inversion, and AVO for gold exploration — Case study from Western Australia

We investigate the potential of using high-resolution seismic methods for rock characterization and for targeting of gold deposits at the St. Ives gold camp. The application of seismic methods in hard-rock environments is challenged by complex structures, intrinsically low signal-to-noise ratio, regolith distortions, and access restrictions. If these issues can be addressed, then the unparalleled resolving power of reflection seismic can be used for mineral exploration. Appropriate spatial sampling of the wavefield combined with a survey geometry design and rigorous data processing to incorporate high fold and long offsets are necessary for creation of high-quality seismic images. In the hard-rock environment of Western Australia, accurate static corrections and multiphase velocity analysis are essential processing steps. This is followed by a rigorous quality control following each processing step. In such a case, we show that the role of reflection seismic could be lifted from mere identification of first-order structures to refined lithological analyses. Five deep boreholes with sonic logs and core sample test data were used to calibrate 2D seismic images. Despite seismic images were produced with relatively robust scaling it was possible to achieve reasonably high seismic-log correlation across three of the tightly spaced boreholes using a single composite wavelet. Amplitude-versus-offset (AVO) analysis indicated that gold-bearing structures may be related to elevated AVO effect and increased reflectivity. Consequently, partial stack analysis and acoustic and elastic inversions were conducted. These results and impedance crossplots were then evaluated against known gold occurrences. While still in the preliminary stages, hard-rock seismic imaging, inversion, and the application of AVO techniques indicated significant potential for targeting mineral reserves.

Bayesian closed-skew Gaussian inversion of seismic AVO data for elastic material properties

Bayesian closed-skew Gaussian inversion is defined as a generalization of traditional Bayesian Gaussian inversion, which is used frequently in seismic amplitude-versus-offset (AVO) inversion. The new model captures skewness in the variables of interest; hence, the posterior model for log-transformed elastic material properties given seismic AVO data might be a skew probability density function. The model is analytically tractable, and this makes it applicable in high-dimensional 3D inversion problems. Assessment of the posterior models in high dimensions requires numerical approximations, however. The Bayesian closed-skew Gaussian inversion approach has been applied on real elastic material properties from a well in the Sleipner field in the North Sea. A comparison with results from traditional Bayesian Gaussian inversion shows that the mean square error of predictions of P-wave and S-wave velocities are reduced by a factor of two, although somewhat less for density predictions.

Integrated geological and geophysical analysis by hierarchical classification: combining seismic stratigraphic and AVO attributes

ABSTRACT The benefits of seismic attribute classification in subsurface studies have been published widely. The approach is usually the same and, in most cases, driven by a two-step procedure – an unsupervised classification and a supervised scheme where training is used to redefine classes based on well-log data flagging a specific fluid or lithology. In parallel to the multi-attribute analysis, interpreters have also benefited from recent advances in computing power, enabling the generation of multi-trace or texture attributes. In these two workflows, the focus is either on the seismic texture facies for seismic stratigraphic purposes, or on the reservoir facies for fluid and lithology mapping. This paper presents a case study in which both texture facies and fluid prediction are linked by performing a hierarchical classification scheme whereby a multi-attribute-based volume, which captures seismic texture information, is combined with amplitude versus offset (AVO) attributes to map fluid response into a single, coherent reservoir facies volume. This methodology is then applied for exploration data screening in offshore Borneo in the Greater Samarang sub-block (East Baram Delta, offshore Sabah, Malaysia). In this case study, the geological analysis, seismic geomorphology, seismic stratigraphy and combined fluid response from AVO attributes facilitate the development of new play concepts in the highstand system tracts and in the morphology generated by incised valleys in shoreface deposits.

Study on attribute characterization for reservoir dynamic monitoring by seismic

Study on characterizing reservoir parameters dynamic variations by time-lapse seismic attributes is the theoretical basis for effectively distinguishing reservoir parameters variations and conducting time-lapse seismic interpretation, and it is also a key step for time-lapse seismic application in real oil fields. Based on the rock physical model of unconsolidated sandstone, the different effects of oil saturation and effective pressure variations on seismic P-wave and S-wave velocities are calculated and analyzed. Using numerical simulation on decoupled wave equations, the responses of seismic amplitude with different offsets to reservoir oil saturation variations are analyzed, pre-stack time-lapse seismic attributes differences for oil saturation and effective pressure variations of P-P wave and P-S converted wave are calculated, and time-lapse seismic AVO (Amplitude Versus Offset) response rules of P-P wave and P-S converted wave to effective pressure and oil saturation variations are compared. The theoretical modeling study shows that it is feasible to distinguish different reservoir parameters dynamic variations by pre-stack time-lapse seismic information, including pre-stack time-lapse seismic attributes and AVO information, which has great potential in improving time-lapse seismic interpretation precision. It also shows that the time-lapse seismic response mechanism study on objective oil fields is especially important in establishing effective time-lapse seismic data process and interpretation scheme.

Shallow seismic AVO variations related to partial water saturation during a pumping test

High‐resolution shallow seismic reflection experiments were conducted during and after a pumping test of an agricultural irrigation well to image the cone of depression. Although variations in the reflection time from the top of the saturated zone were not observed, amplitude‐versus‐offset (AVO) analysis revealed changes in reflection amplitude responses that correlate temporally and spatially to expected changes to the partially saturated zone induced by the pumping and recovery of the aquifer. The AVO responses exhibit dependence on aquifer drawdown and recovery cycles and the distance from the pumping well. We propose that near‐surface soil heterogeneity and relatively rapid changes in the water table elevation during irrigation cycles caused a thickening of the partially saturated zone above the water table, which resulted in detectable changes in seismic reflection amplitudes. This study offers insights about the response of shallow seismic reflections to changes in subsurface water saturation and the potential application of seismic techniques to hydrogeophysical problems.

Stochastic reservoir characterization using prestack seismic data

Reservoir characterization must be based on information from various sources. Well observations, seismic reflection times, and seismic amplitude versus offset (AVO) attributes are integrated in this study to predict the distribution of the reservoir variables, i.e., facies and fluid filling. The prediction problem is cast in a Bayesian setting. The a priori model includes spatial coupling through Markov random field assumptions and intervariable dependencies through nonlinear relations based on rock physics theory, including Gassmann's relation. The likelihood model relating observations to reservoir variables (including lithology facies and pore fluids) is based on approximations to Zoeppritz equations. The model assumptions are summarized in a Bayesian network illustrating the dependencies between the reservoir variables. The posterior model for the reservoir variables conditioned on the available observations is defined by the a priori and likelihood models. This posterior model is not analytically tractable but can be explored by Markov chain Monte Carlo (MCMC) sampling. Realizations of reservoir variables from the posterior model are used to predict the facies and fluid‐filling distribution in the reservoir. A maximum a posteriori (MAP) criterion is used in this study to predict facies and pore‐fluid distributions. The realizations are also used to present probability maps for the favorable (sand, oil) occurrence in the reservoir. Finally, the impact of seismic AVO attributes—AVO gradient, in particular—is studied.The approach is demonstrated on real data from a turbidite sedimentary system in the North Sea. AVO attributes on the interface between reservoir and cap rock are extracted from 3D seismic AVO data. The AVO gradient is shown to be valuable in reducing the ambiguity between facies and fluids in the prediction.

Compressional velocity structure and Poisson's ratio in marine sediments with gas hydrate and free gas by inversion of reflected and refracted seismic data (South Shetland Islands, Antarctica)

Abstract A Bottom Simulating Reflector (BSR) on the South Shetland Margin (Antarctic Peninsula) was surveyed, within the Progetto Nazionale di Ricerche in Antartide (PNRA). High resolution multichannel (MCS) reflection profiles were acquired, and a three-component Ocean Bottom Seismograph (OBS) was deployed where the BSR was particularly strong. The compressional velocity field associated to the BSR was determined by the inversion of travel times of reflected (MCS data) and refracted (OBS data) events. Information on shear wave velocities was extracted from the horizontal components of the OBS records. The analysis indicates the presence of velocity anomalies both above and below the BSR that are not related to the lithologic characteristics of the sedimentary column, but can be associated to gas hydrate and free gas presence in pore space. Amplitude Versus Offset (AVO) analysis was performed on Common Depth Point gathers, which correspond to the OBS position. The study determined reflection coefficient trends that provided qualitative information about gas hydrate and free gas abundance. A theoretical model for elastic porous media was applied to quantify amounts of gas hydrate and free gas. The resulting theoretical velocity curves were compared to interval velocity obtained by seismic inversion. A quantitative estimation of free gas and gas hydrates trapped in the sediment pore spaces was made by interpreting velocity anomalies with respect to reference velocity curves (normally consolidated marine terrigenous sediments). The comparison of the results obtained by these independent methods (seismic inversion, AVO analysis, and theoretical model) gives consistent values of Poisson's ratio and gas hydrate and free gas estimation.

AVO as an Exploration Tool in the Penola Trough, Otway Basin

In 1988, Katnook-1 discovered gas in the basal Eumeralla Formation in the Penola Trough. All subsequent commercial discoveries have been within the underlying Crayfish Group. Amplitude-versus-offset (AVO) analysis performed on single gather records correctly predicted the subsequent discovery of gas within the Crayfish Group in the Katnook-2 and Ladbroke Grove-1 wells. Seismic recorded since 1990 has generally better quality data which are more suitable for AVO analysis. Two lines were recorded in 1993 over the Katnook Field, tied to the three Katnook wells. Only a small AVO effect was predicted at some locations from modelling using the well data, which was probably due to the poor quality well logs. The seismic AVO analysis, however, using all gather records, produced clear anomalies at both reservoir levels which approximately matched the predicted extent of the gas in the field from structural mapping. The subsequent Katnook-4 appraisal well confirmed the presence of gas at these levels, but unfortunately was not commercial. AVO and inversion were also run over the Haselgrove Gas Field prior to its discovery in 1994. AVO anomalies are seen at both Katnook reservoir levels, but the strong basal Eumeralla Formation anomaly is interpreted to be due to a clean, water saturated sand rather than gas. The anomalies at the top Pretty Hill Sandstone level are more consistent with structure although they extend below mapped closure. Subsequent reprocessing using pre-stack migration prior to AVO analysis produced anomalies which closely match the actual gas column height, and are within the zone of strong seismic amplitudes at this level. AVO anomalies in the area appear to be caused by both clean, water filled sands and the presence of hydrocarbons. Seismic inversion can help the prediction of sand quality variations, and the mapped extent of structural closure can be used to identify those AVO anomalies more likely to be related to hydrocarbons. Pre-stack time migration prior to AVO processing is essential in most cases. Unfortunately, AVO anomalies also occur in reservoirs with low gas saturations or low reservoir permeability. Despite these drawbacks AVO with inversion has proven to be a valuable exploration tool in the Penola Trough. No gas discoveries have yet been made which are not associated with an AVO anomaly.

Seismic AVO analysis of a permian gas sand at Kerna field, Cooper Basin, SA

The Kerna gas field is located in the south-central part of the Cooper Basin close to the large Dullingari and Toolachee Fields. Kerna is a domal anticline and contains gas structurally trapped within sandstones of the Early Permian Patchawarra Formation. The overlying Epsilon Formation sands also contain gas which may be stratigraphically trapped around the south and west flanks of the field.Seismic reflection amplitudes are used to map the extent of this Epsilon gas sand. Seismic modelling studies show that the gas sand displays an amplitude-versus-offset (AVO) response which distinguishes it from a wet sand or from a coal bed at the same stratigraphic level. Constructive and destructive interference from the top and base of the gas sand, and from overlying coal seams, have a marked effect on the overall seismic stack response of the target horizon. The modelled AVO response shows a good correlation with AVO changes on cd.p. gathers from seismic lines across the area.The spatial distribution of the AVO anomalies (AVO increases), and of the overall seismic stack response, has been mapped across the field and can be used to locate future appraisal and exploration wells. This study has implications for other areas of the Cooper Basin where adequate separation between coal beds and gas sands allows the AVO effect of the latter to be observed. These AVO effects can then be used as a direct indicator of gas in stratigraphic or even structural traps.