Seismic Amplitude Data Research Articles

Lithology and fluid prediction from prestack seismic data using a Bayesian model with Markov process prior

ABSTRACTWe invert prestack seismic amplitude data to find rock properties of a vertical profile of the earth. In particular we focus on lithology, porosity and fluid. Our model includes vertical dependencies of the rock properties. This allows us to compute quantities valid for the full profile such as the probability that the vertical profile contains hydrocarbons and volume distributions of hydrocarbons. In a standard point wise approach, these quantities can not be assessed. We formulate the problem in a Bayesian framework, and model the vertical dependency using spatial statistics. The relation between rock properties and elastic parameters is established through a stochastic rock model, and a convolutional model links the reflectivity to the seismic. A Markov chain Monte Carlo (MCMC) algorithm is used to generate multiple realizations that honours both the seismic data and the prior beliefs and respects the additional constraints imposed by the vertical dependencies. Convergence plots are used to provide quality check of the algorithm and to compare it with a similar method. The implementation has been tested on three different data sets offshore Norway, among these one profile has well control. For all test cases the MCMC algorithm provides reliable estimates with uncertainty quantification within three hours. The inversion result is consistent with the observed well data. In the case example we show that the seismic amplitudes make a significant impact on the inversion result even if the data have a moderate well tie, and that this is due to the vertical dependency imposed on the lithology fluid classes in our model. The vertical correlation in elastic parameters mainly influences the upside potential of the volume distribution.The approach is best suited to evaluate a few selected vertical profiles since the MCMC algorithm is computer demanding.

Structural curvature versus amplitude curvature

Because they are second-order derivatives, seismic curvature attributes can enhance subtle information that may be difficult to see using first-order derivatives such as the dip magnitude and the dip-azimuth attributes. As a result, these attributes form an integral part of most seismic interpretation projects. This conventional computation of curvature may be termed as structural curvature, as lateral second-order derivatives of the structural component of seismic time or depth of reflection events are used to generate them. In this study, we explore the case of applying lateral second-order derivatives on the amplitudes of seismic data along the reflectors. We refer to such computation as amplitude curvature. For volumetric structural curvature we compute first derivatives in the inline and crossline components of structural dip. For amplitude curvature, we apply a similar computation to the inline and crossline components of the energy-weighted amplitude gradients, which represent the directional measures of amplitude variability. Because of limits to lateral resolution, application of amplitude curvature computation to real seismic data results in greater lateral resolution than structural curvature. The images are mathematically independent of each other and thus highlight different features in the subsurface, but are often correlated through the underlying geology.

Fracture mapping and modelling in shale-gas target in the Cooper Basin, South Australia

The success story of a shale-gas reserve development in the United States is triggering a strong industry focus towards similar plays in Australia. The Cooper Basin (located at the border of South Australia and Queensland) and the Otway Basin (extending both onshore and offshore South Australia and Victoria) could be prime targets to develop shale-gas projects. The Cooper Basin, a late-Carboniferous to mid-Triassic basin, is the largest onshore sedimentary basin producing oil and gas from tight conventional reservoirs with low permeability. Fracture stimulation programs are used extensively to produce the oil and gas. Furthermore, new exploration strategies are now targeting possible commercial gas hosted in low-permeability Permian shale units. To maximise production, the development of shale-gas prospects requires a good understanding of the: 1. structure of the reservoirs; 2. mechanical properties of the stratigraphy; 3. fracture geometry and density; 4. in-situ stress field; and, 5. fracture stimulation strategies. In this study, we use a combination of seismic mapping techniques–including horizon and attribute mapping, and an analysis of wellbore geophysical logs–to best constrain the existing fracture network in the basins. This study is based on the processing and analysis of a 3D seismic cube–the Moomba Big Lake survey–which is located in the southwestern part of the Cooper Basin. This dataset covers an area encompassing both a structurally complex setting in the vicinity of a major fault to the SE of the survey, and an area of more subtle deformation corresponding to the southernmost part of the Nappamerri Trough. Structural fabrics trending ˜NW–SE and NE–SW, which are not visible on the amplitude seismic data, are revealed by the analysis of the seismic attributes–namely a similarity (equivalent to a coherency cube), dip steering and maximum curvature attributes. These orientations are similar to those of natural fractures mapped from borehole images logs, and can therefore be interpreted as imaging natural fractures across the Moomba-Big Lake area. This study is the first of its kind able to detect possible fractures from seismic data in the Cooper Basin. The methodology developed here can offer new insights into the structure of sedimentary basins and provide crucial parameters for the development of tight reservoirs. In parallel, a tentative forward model of the generation of a fracture network following a restoration of the Top Roseneath horizon was carried out. The relatively good correlation between the fracture orientations generated by the model and the fractures mapped from geophysical data shows that fractures in the Moomba-Big Lake area may have formed during either a N–S compressive principal horizontal stress, or an E–W compressive principal horizontal tectonic stress regime. In addition, the orientations of the fracture interpreted through this study are also compatible with a generation under the present day stress regime described in this part of the basin, with an maximal horizontal stress trending E–W.

An initial acoustic impedance modeling method based on seismic attributes

It is common that an initial impedance model should be created first, while performing acoustic impedance inversion. The traditional modeling is horizontally interpolated using inverse distance power method for multiple wells, and vertically controlled by seismic horizons. This method was relatively simple, and could not reflect the seismic facies changes in complex geological conditions, inversion accuracy was not high.Based on seismic attributes, the method introduced here calculated the weight coefficient with the amplitude of seismic data attributes, waveform correlation coefficient or other seismic attributes to build initial impedance model. The model built with this method could vertically reflect the trend of seismic facies changes and horizontally overcome the mismatching between local geological phenomenon and seismic horizons. This initial model built could descript more detailed changes in the seismic facies, and enhance inversion accuracy under the complex geological conditions.

3D porosity prediction from seismic inversion and neural networks

In this work, we address the problem of transforming seismic reflection data into an intrinsic rock property model. Specifically, we present an application of a methodology that allows interpreters to obtain effective porosity 3D maps from post-stack 3D seismic amplitude data, using measured density and sonic well log data as constraints. In this methodology, a 3D acoustic impedance model is calculated from seismic reflection amplitudes by applying an L 1-norm sparse-spike inversion algorithm in the time domain, followed by a recursive inversion performed in the frequency domain. A 3D low-frequency impedance model is estimated by kriging interpolation of impedance values calculated from well log data. This low-frequency model is added to the inversion result which otherwise provides only a relative numerical scale. To convert acoustic impedance into a single reservoir property, a feed-forward Neural Network (NN) is trained, validated and tested using gamma-ray and acoustic impedance values observed at the well log positions as input and effective porosity values as target. The trained NN is then applied for the whole reservoir volume in order to obtain a 3D effective porosity model. While the particular conclusions drawn from the results obtained in this work cannot be generalized, such results suggest that this workflow can be applied successfully as an aid in reservoir characterization, especially when there is a strong non-linear relationship between effective porosity and acoustic impedance.

Ensemble-based conditioning of reservoir models to seismic data

While 3D seismic has been the basis for geological model building for a long time, time-lapse seismic has primarily been used in a qualitative manner to assist in monitoring reservoir behavior. With the growing acceptance of assisted history matching methods has come an equally rising interest in incorporating 3D or time-lapse seismic data into the history matching process in a more quantitative manner. The common approach in recent studies has been to invert the seismic data to elastic or to dynamic reservoir properties, typically acoustic impedance or saturation changes. Here we consider the use of both 3D and time-lapse seismic amplitude data based on a forward modeling approach that does not require any inversion in the traditional sense. Advantages of such an approach may be better estimation and treatment of model and measurement errors, the combination of two inversion steps into one by removing the explicit inversion to state space variables, and more consistent dependence on the validity of assumptions underlying the inversion process. In this paper, we introduce this approach with the use of an assisted history matching method in mind. Two ensemble-based methods, the ensemble Kalman filter and the ensemble randomized maximum likelihood method, are used to investigate issues arising from the use of seismic amplitude data, and possible solutions are presented. Experiments with a 3D synthetic reservoir model show that additional information on the distribution of reservoir fluids, and on rock properties such as porosity and permeability, can be extracted from the seismic data. The role for localization and iterative methods are discussed in detail.

Multiple seismic attribute analyses for determination of bottom simulating reflector of gas hydrate seismic data in the Ulleung Basin of Korea

The bottom simulating reflector (BSR), the boundary between the gas hydrate and the free gas zone, is considered to be the most common evidence in seismic data analysis for gas hydrate exploration. Multiple seismic attribute analyses of reflectivity and acoustic impedance from the post-stack deconvolution and complex analysis of instantaneous attribute properties including the amplitude envelope, instantaneous frequency, phase, and first derivative of the amplitude of seismic data have been used to effectively confirm the existence of a BSR as the base of gas hydrate stability zone. In this paper, we consider individual seismic attribute analysis and integrate the results of those attributes to locate the position of the BSR. The outputs from conventional seismic data processing of the gas hydrate data set in the Ulleung Basin were used as inputs for multiple analyses. Applying multiple attribute analyses to the individual seismic traces showed that the identical anomalies found in two-way travel time (TWT) between 3.1 and 3.2 s from the results of complex analyses and l 1 norm deconvolution indicated the location of the BSR.

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.

Seismic Facies Identification and Classification Using Simple Statistics

Summary The identification and mapping of rock facies is important to reliable reservoir characterization. Traditionally, facies identification and mapping are based on inspection of core data and/or well-log signatures, a procedure that has subjective aspects because it is relies on samples from only a very small portion of the reservoir. Such identification is also difficult to perform at the onset of the exploration stage because of lack of sufficient well data. This paper demonstrates a simple practical approach to identify and classify facies from seismic-amplitude data using basic statistical concepts. Within a geologic facies, measured properties [in this case acoustic impedance (AI)] are assumed to differ mainly as a result of random additive events and are modeled by a normal distribution, as justified by the central-limit theorem. The facies are identified by estimating the combination of facies volume fractions and distribution parameters (means and standard deviations of the facies probability-density function) that best fit the population distribution of AI. A simple form of Bayes theorem is then used to compute the probability of occurrence of each of the facies at the measured locations. This generates a volume of facies probabilities corresponding to the seismic volume. Such a volume can be used to perform facies-specific petrophysical analysis or be a starting point to generate multiple realizations of petrophysical properties. The approach is simple and transparent to use, with no significant computational requirements even on large data sets. We describe an application of the procedure to a synthetic reference data set and a Gulf of Mexico AI data set. Mapped probabilities of the individual facies show the spatial continuity and geologic character of the underlying depositional environment. Property values within the mapped regions are substantially less variable than the original data across the entire region. The within-facies semivariograms exhibit much less spatial correlation than across all facies. Since the facies are mapped across an exhaustive data volume, this approach considerably reduces the need for the geostatistical construction of property distributions within them as long as a high correlation exists between the seismic attribute and petrophysical properties.

Lava discharge rate and effusive pattern at Piton de la Fournaise from MODIS data

We analysed the effusive activity of 15 eruptions of Piton de la Fournaise by using the data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) during 2003–2007 period. Thermal anomalies were detected by adjusting the values of the Normalised Thermal Index (NTI) threshold [Wright, R.L., Flynn, H., Garbeil, A.J.L., Harris Pilger, E., 2002. Automated volcanic eruption detection using MODIS. Remote Sens. Environ. 82: 135–155.] in accord to the seasonal and topographic variations of the background temperature at Piton de la Fournaise. Each satellite overpass, has been classified according to the presence of clouds and the satellite viewing geometry. The analyzed data indicate that at Piton de la Fournaise only 10% of MODIS overpasses occurred in optimal conditions (clear sky and satellite zenith < 40°). However this classification allowed us to use the 4 μm radiance to estimate time average of lava discharge rates (TADR) for most of the analysed eruptions. These data has been used to compare the inferred effusive pattern with the real time seismic amplitude data (RSAM) recorded during the same events. We found that summit eruptions, characterised by a lower discharge rate (< 2 m 3s − 1 ), induce a separation of the gas phase which translate into a decoupling between TADR and RSAM. This regime coupled with the low magma ascent rate and the typical steady effusion of these eruptions imply a very low pressurization of the shallower reservoir which is consistent with a direct overflow of the magma supplied from depth. Conversely, the distal eruptions show a TADR linearly correlated with the RSAM thus indicating a more homogeneous degassing regime and the absence of gas accumulation process within the shallow reservoir. The high initial TADR (> 20 m 3 s − 1 ) and the following vanishing phase indicate that distal eruptions are triggered when a critical overpressure is reached (>5 MPa). This last seems to be increased during the whole analysed period up to the onset of the April 2007 which led to the collaps of the Dolomieu crater. Finally we propose that the recent activity of PdF may result from a persistent loading of the shallow reservoir with a magma supply rate which increased from 1135 kg s − 1 to 4310 kg s − 1 during the period between 2003 and 2007.

Interpretation and mapping of a stratigraphic play using 3D seismic data and attributes in central Saudi Arabia

Interpretation of three-dimensional (3D) seismic data from the northern part of central Saudi Arabia allowed mapping of the Permo-Carboniferous Unayzah Formation's aeolian sand deposits and fluvial channels. These types of depositional environments have been associated frequently with better reservoir-quality sandstones within Saudi Arabia. The depositional setting of the Unayzah reservoirs can be highly variable and range from glacial, to lacustrine, to meandering fluvial, to aeolian, to braided stream. Seismic amplitude data were instrumental in mapping a truncation of the upper Unayzah reservoir against the overlying Pre-Khuff Unconformity. The use of seismic attributes, such as coherence and curvature, indicated the existence of faulting and a fluvial channel network at the top of the Unayzah Formation. The integration of well and seismic amplitude data, via acoustic impedance inversion, revealed the direction of potentially higher porosity fairways within the channel system. The structural and depositional architecture depicted in this study is being appraised through drilling of an exploration well.

Value of information of seismic amplitude and CSEM resistivity

We propose a method for computing the value of information in petroleum exploration, a field in which decisions regarding seismic or electromagnetic data acquisition and processing are critical. We estimate the monetary value, in a certain context, of a seismic amplitude or electromagnetic-resistivity data set before purchasing the data. The method is novel in the way we incorporate spatial dependence to solve large-scale, real-world problems by integrating the decision-theoretical concept of value of information with rock physics and statistics. The method is based on a statistical model for saturation and porosity on a lattice along the top reservoir. Our model treats these variables as spatially correlated. The porosity and saturation are tied to the seismic and electromagnetic data via nonlinear rock-physics relations. We efficiently approximate the posterior distribution for the reservoir variables in a Bayesian model by fitting a Gaussian at the posterior mode for transformed versions of saturation and porosity. The value of information is estimated based on the prior and posterior distributions, the possible revenues from the reservoir, and the cost of drilling wells. We illustrate the method with three examples.

A study to assess the value of post-stack seismic amplitude data in forecasting fluid production from a Gulf-of-Mexico reservoir

This paper describes a study undertaken to appraise the reliability of spatially complex hydrocarbon reservoir models constructed with the use of post-stack seismic amplitude data and well logs. Developments center about the interpretation of data acquired in an active hydrocarbon field in the Gulf of Mexico. The availability of measured time records of fluid production and pressure depletion provides an independent way to quantify the accuracy and reliability of several methods commonly employed to construct static reservoir models. We make use of geostatistical inversion to construct spatial distributions of porosity and permeability that simultaneously honor well logs and post-stack seismic amplitude data. The constructed reservoir models are compared against models constructed with conventional geostatistical procedures that do not make use of seismic amplitude data or else that use a simple statistical correlation between petrophysical properties and seismic-inverted acoustic impedances. We perform multi-phase fluid-flow simulations to assess the consistency of the constructed reservoir models against the measured time record of flow rates of gas/water and shut-in well pressures. For the hydrocarbon field under consideration, the joint stochastic inversion of well logs and post-stack seismic amplitude data yields the closest match to dynamic measurements of fluid production and pressure depletion. We found that the spatial continuity of permeability exhibited the largest influence on the behavior of fluid production and pressure depletion with time. Perturbations to the relationships between porosity, permeability, and acoustic impedance produced significant variations in the simulated time record of fluid production. Finally, we found that the degree of spatial variability of permeability and porosity, and presence of permeability anisotropy were substantially more significant in the prediction of fluid production than variability of relative permeability and capillary pressure.

The impact of random noise on seismic wavelet estimation

Deterministic seismic wavelet (or source signature) estimation is a mature subject, and is commonly accomplished by deconvolution using surface seismic amplitude data and borehole wireline log data. The seismic wavelet is important to reservoir geophysics/quantitative interpretation for use in inversion, synthetic seismograms, wavelet processing, etc. Hence, the quality of the wavelet estimate is of interest. Many factors affect wavelet uncertainty, including both seismic and well-log data quality, the latter which in turn affects the reflection coefficients estimate.

Probabilistic seismic inversion based on rock-physics models

A site-specific rock-physics transform from porosity, mineralogy, and pore fluid to elastic-wave velocities is used to invert seismic amplitude data for clay content, total porosity, and saturation. The implementation is Bayesian and produces probabilistic values of the reservoir properties from seismic measurements and well data. This method focuses on an exploration setting where minimal data exist. Two key assumptions reduce the problem and keep the prior information as noncommittal as possible. First, a prior interpretation of the seismic data is required that provides a geobody on which to perform the inversion. Second, the reservoir thickness is assumed to be constant, as are the rock properties within the reservoir. The prior distributions of the reservoir properties are assumed to be uncorrelated and independent, although this is not an essential assumption. Central to theinversion is the generation of a complete set of earth models derived from the prior distribution. A site-specific rock-physics model translates these properties (clay content, porosity, and saturation) into the elastic domain. A complete set of forward seismic models accompanies the earth models, and these seismic models are compared to the real data on a trace-by-trace basis. The reservoir properties corresponding to the seismic models that match the real data within predefined errors are used to construct the posterior. This method was tested on well and seismic data from offshore western South Africa. Initial results at calibration and test wells indicate an overprediction of porosity and uncertain predictions of clay content and saturation. This is a result of the constant-thickness assumption. However, a highly negative correlation between porosity and thickness is predicted, which manifests the success of this method.

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.

O papel da inversão para a impedância acústica no processo de caracterização sísmica de reservatórios

O processo de caracterizacao de reservatorios consiste na determinacao tridimensional e quantitativa da estrutura e das propriedades petrofisicas de um campo de petroleo. A utilizacao do dado sismico 3D neste processo tem se tornado cada vez mais comum principalmente na identificacao da forma e do tamanho dos corpos de areia que constituem o reservatorio. Porem em alguns casos como nos reservatorios turbiditicos de aguas profundas da Bacia de Campos, que sao caracterizados por uma complexa distribuicao dos corpos de areia e por camadas com espessura subsismica, a utilizacao do dado sismico convencional em amplitude pode acarretar serios erros na definicao de um modelo para o reservatorio. Para superar os problemas causados pela limitacao da resolucao vertical do dado sismico e necessario gerar modelos que integrem todas as informacoes disponiveis sobre o reservatorio. A maneira mais efetiva de se integrar o dado sismico no processo de caracterizacao de reservatorios e por meio da geracao de modelos de impedância acustica derivados do processo de inversao sismica. O objetivo deste trabalho e mostrar como a inversao sismica para a impedância acustica pode auxiliar e melhorar o processo de caracterizacao de reservatorios, comparando os resultados obtidos por meio da aplicacao de dois metodos, a inversao recursiva e a inversao sparse-spike. Os metodos de inversao sismica aqui estudados sao aplicados em um modelo sintetico de referencia, que possui a forma de uma cunha, modelo esse que representa de forma realista afinamentos estratigraficos e feicoes como pinchouts, frequentemente encontrados em reservatorios turbiditicos de aguas profundas. Com os resultados obtidos podem ser vistas vantagens em se utilizar o processo de inversao sismica tanto na determinacao da geometria dos corpos que formam o reservatorio, como tambem na obtencao das propriedades petrofisicas, e por consequencia modelos mais precisos sao gerados e as previsoes de comportamento do campo podem ser feitas de uma maneira mais efetiva.

AVA simultaneous inversion of partially stacked seismic amplitude data for the spatial delineation of lithology and fluid units of deepwater hydrocarbon reservoirs in the central Gulf of Mexico

This paper describes the successful application of amplitude-versus-angle (AVA) inversion of prestack-seismic amplitude data to detect and delineate deepwater hydrocarbon reservoirs in the central Gulf of Mexico. Detailed AVA fluid/lithology sensitivity analysis was conducted to assess the nature of AVA effects in the study area based on well-log data. Standard techniques such as crossplot analysis, Biot-Gassmann fluid substitution, AVA reflectivity modeling, and numerical simulation of synthetic gathers were part of the AVA sensitivity analysis. Crossplot and Biot-Gassmann analyses indicate significant sensitivity of acoustic properties to fluid substitution. AVA reflectivity and angle-gather modeling indicate that the shale/sand interfaces represented by the top and base of the M-10 reservoir are associated with typical Class III AVA responses caused by relatively low-impedance gas-bearing sands. Consequently, prestack seismic inversion provided accurate and reliable quantitative information about the spatial distribution of lithology and fluid units within the turbidite reservoirs based on the interpretation of fluid/lithology-sensitive modulus attributes. From the integration of inversion results with analogous depositional models, the M-series reservoirs were interpreted as stacked terminal turbidite lobes within an overall fan complex. This interpretation is consistent with previous regional stratigraphic/depositional studies.

Using time-lapse seismic amplitude data to detect variations of pore pressure and fluid saturation due to oil displacement by water: a numerical study based on one-dimensional prestack inversion

We describe a numerical study performed to appraise the ability of seismic amplitude data to infer the time evolution of pore pressure and fluid saturation due to hydrocarbon production. To this end, we construct a synthetic, spatially heterogeneous hydrocarbon reservoir model that is subject to numerical simulation of multiphase fluid flow. Hydrocarbon production is assumed in the form of one water-injection well and four oil-producing wells. The synthetic reservoir model exhibits average porosities of 20% and poses significant vertical resolution constraints to the usage of seismic amplitude data to ascertain variations of pore pressure and fluid saturation. We assume the availability of migrated prestack seismic amplitude and use one-dimensional models to simulate trace by trace the seismic amplitude data before and after the onset of production. One-dimensional seismic amplitude data are simulated in time-lapse mode making use of a rock physics model that includes the effect of differential compaction between sands and shales as a function of depth of burial. The sensitivity study presented in this paper is based on one-dimensional inversion and hence sheds light on the vertical resolution properties of noisy seismic amplitude data. Multiphase fluid-flow parameters have a measurable impact on fluid saturation and pore pressure and hence on the spatial distribution and time evolution of elastic parameters. However, the inverted spatial distributions of elastic parameters at best correlate with smooth spatial averages of the actual distributions of pore pressure and fluid saturation. Because for the case under consideration time-lapse seismic amplitude variations are of the order of 5%, such a correlation would be difficult, if not impossible, to ascertain without the use of one-dimensional inversion. We show that the elastic parameters inverted from prestack seismic amplitude data provide more degrees of freedom to discriminate between time variations of pore pressure and fluid saturation in the reservoir compared to distributions of acoustic impedance inverted from poststack seismic amplitude data.

Enforcing smoothness and assessing uncertainty in non‐linear one‐dimensional prestack seismic inversion

ABSTRACTEstimation of elastic properties of rock formations from surface seismic amplitude measurements remains a subject of interest for the exploration and development of hydrocarbon reservoirs. This paper develops a global inversion technique to estimate and appraise 1D distributions of compressional‐wave velocity, shear‐wave velocity and bulk density, from normal‐moveout‐corrected PP prestack surface seismic amplitude measurements. Specific objectives are: (a) to evaluate the efficiency of the minimization algorithm (b) to appraise the impact of various data misfit functions, and (c) to assess the effect of the degree and type of smoothness criterion enforced by the inversion. Numerical experiments show that very fast simulated annealing is the most efficient minimization technique among alternative approaches considered for global inversion. It is also found that an adequate choice of data misfit function is necessary for a reliable and efficient match of noisy and sparse seismic amplitude measurements. Several procedures are considered to enforce smoothness of the estimated 1D distributions of elastic parameters, including predefined quadratic measures of length, flatness and roughness.Based on the general analysis of global inversion techniques, we introduce a new stochastic inversion algorithm that initializes the search for the minimum with constrained random distributions of elastic parameters and enforces predefined autocorrelation functions (semivariograms). This strategy readily lends itself to the assessment of model uncertainty. The new global inversion algorithm is successfully tested on noisy synthetic amplitude data. Moreover, we present a feasibility analysis of the resolution and uncertainty of prestack seismic amplitude data to infer 1D distributions of elastic parameters measured with wireline logs in the deepwater Gulf of Mexico. The new global inversion algorithm is computationally more efficient than the alternative global inversion procedures considered here.