Seismic Amplitude Data Research Articles

Amplitude variation with offset inversion using the reflectivity method

Most existing amplitude variation with offset (AVO) inversion methods are based on the Zoeppritz’s equation or its approximations. These methods assume that the amplitude of seismic data depends only on the reflection coefficients, which means that the wave-propagation effects, such as geometric spreading, attenuation, transmission loss, and multiples, have been fully corrected or attenuated before inversion. However, these requirements are very strict and can hardly be satisfied. Under a 1D assumption, reflectivity-method-based inversions are able to handle transmission losses and internal multiples. Applications of these inversions, however, are still time-consuming and complex in computation of differential seismograms. We have evaluated an inversion methodology based on the vectorized reflectivity method, in which the differential seismograms can be calculated from analytical expressions. It is computationally efficient. A modification is implemented to transform the inversion from the intercept time and ray-parameter domain to the angle-gather domain. AVO inversion is always an ill-posed problem. Following a Bayesian approach, the inversion is stabilized by including the correlation of the P-wave velocity, S-wave velocity, and density. Comparing reflectivity-method-based inversion with Zoeppritz-based inversion on a synthetic data and a real data set, we have concluded that reflectivity-method-based inversion is more accurate when the propagation effects of transmission losses and internal multiples are not corrected. Model testing has revealed that the method is robust at high noise levels.

The influence of pore pressure in assessing hydrocarbon prospectivity: a review

Assessing the prospectivity of a basin or a play is a complex process that combines a multitude of geological, geomechanical and geophysical analyses with the aim to de-risk whether a particular basin/play should be explored further. However, it is possible to group the analyses under five simple terms: source, charge, reservoir, trap, and seal. In basic terms, if a basin/play can be demonstrated to have a source of hydrocarbons, a reservoir to accept the charge and a trap and seal to limit the migration of the hydrocarbons any further then the ‘opportunity’ has been shown to be prospective for hydrocarbon exploration, i.e. de-risking has occurred. Typical elements of this de-risking process would include assessing the presence and quality of the source rock or building a structural and stratigraphic model from seismic amplitude data. Other components would be modelling porosity for instance. However, the particular focus of this paper is that many of the other components that need to be understood and modelled as part of the assessment of prospectivity are related to the pressure regime within a basin/acreage block in which a prospect is located. The focus of this paper is, therefore, to highlight and review those aspects of hydrocarbon prospectivity that pertain to reservoir quality, migration, maturation, prospect identification and hydrocarbon retention that are demonstrably influenced by pore pressure (Figure 1). It is important to note that whilst understanding the reservoir forms a key focus within such studies of prospectivity, the pore pressure within the bounding shales (relative to the reservoir) is also important to understand aside from the implications for well planning.

Rock-physics and seismic-inversion based reservoir characterization of the Haynesville Shale

Seismic reservoir characterization of unconventional gas shales is challenging due to their heterogeneity and anisotropy. Rock properties of unconventional gas shales such as porosity, pore-shape distribution, and composition are important for interpreting seismic data amplitude variations in order to locate optimal drilling locations. The presented seismic reservoir characterization procedure applied a grid-search algorithm to estimate the composition, pore-shape distribution, and porosity at the seismic scale from the seismically inverted impedances and a rock-physics model, using the Haynesville Shale as a case study. All the proposed rock properties affected the seismic velocities, and the combined effects of these rock properties on the seismic amplitude were investigated simultaneously. The P- and S-impedances correlated negatively with porosity, and the V P/V S correlated positively with clay fraction and negatively with the pore-shape distribution and quartz fraction. The reliability of these estimated rock properties at the seismic scale was verified through comparisons between two sets of elastic properties: one coming from inverted impedances, which were obtained from simultaneous inversion of prestack seismic data, and one derived from these estimated rock properties. The differences between the two sets of elastic properties were less than a few percent, verifying the feasibility of the presented seismic reservoir characterization.

Probabilistic falsification of prior geologic uncertainty with seismic amplitude data: Application to a turbidite reservoir case

Geophysical subsurface modeling is often highly uncertain due to limited data resolution. At the same time, a wealth of geologic information, often from databases and outcrop studies, is available to state prior uncertainty on key geologic modeling parameters. In most inversion procedures, these uncertainties are ignored and only a limited number of geologic scenarios are considered. We have developed a workflow, inspired by a Popper-Bayes philosophy that aims at probabilistically updating prior geologic parameters uncertainty with data without the need for inversion or iterative data conditioning. Our approach consists of stating a wide prior model of uncertainty (in rock physics and facies), and generating a set of facies models and their corresponding geophysical responses (here the seismic response) by forward simulation. Then, a global measure of similarity is defined between any two generated seismic responses and the field data. The proposed measure, based on the wavelet transform decomposition, analyzes differences in patterns found in the seismic data and aims at comparing seismic images as a whole, avoiding any local trace-by-trace comparison. Based on this global measure of similarity, our procedure identifies the geologic interpretations that are unlikely given the observed seismic data. The proposed approach was applied and validated using seismic data from a synthetic example and an offshore reservoir in west Africa. The uncertainty included geologic parameters, such as infill channel size, proportion, and sinuosity, and geophysical parameters, such as the rock physics model and the wavelet in the forward seismic model. The synthetic example allowed for the validation of the methodology using rejection sampling. For the offshore reservoir, updated probabilities were obtained for each uncertain parameter, and some of the prior geologic interpretations were found to be inconsistent with the available seismic amplitude data cube (e.g., narrow channel width).

Mapping of alteration zones with seismic-amplitude data and well logs in the hard-rock environment of the Keefe Lake area, Athabasca Basin, Canada

Optical televiewer (OTV) and full-wave sonic (FWS) data sets acquired in two boreholes from the Keefe Lake property of Atom Energy Inc. (AEI) provided a unique opportunity to study the lithologic units through analysis of P- and S-wave velocities and elastic rock properties derived from them (Poisson's ratio, lambda, and mu). This approach is a first attempt to describe petrophysical properties for the sandstone sediments and underlying crystalline Proterozoic rocks of the eastern Athabasca Basin. Wireline measurements penetrated through the entire (180-m) thickness of the basin fill and deep into the basement (357 m and 552 m), intersecting several fracture and alteration zones. Such zones are considered possible locations of uranium mineralization in the Athabasca Basin. Seismic attributes (amplitude envelope and cosine instantaneous phase) can be used in the hard-rock environment. The characteristic values of fracture and alteration zones can by analyzed by crossplotting the elastic properties derived from the FWS data. After insertion of the elastic-property logs into the closest seismic section, the probable spatial extents of three anomalous zones revealed in the vicinity of the boreholes are investigated. The results of amplitude-variation-with-offset (AVO) modeling carried out based on petrophysical properties obtained from the basement show that clay-filled fracture zones in the hard-rock environment of the study area are associated with increasing, anomalous AVO responses.

Techniques and best practices in multiattribute display

All color monitors display images by mixing red, green, and blue (RGB) components. These RGB components can be defined mathematically in terms of hue, lightness, and saturation (HLS) components. A fourth alpha-blending (also called opacity) component provides a means to corender multiple images. Most, but not all, modern commercial interpretation workstation software vendors provide multiattribute display tools using an opacity model. A smaller subset of vendors provide tools to interactively display two or three attributes using HLS, CMY, and RGB color models. I evaluated a technique (or trick) to simulate the HLS color model using monochromatic color bars and only opacity. This same trick only approximates true color blending of RGB or CMY components. There are three basic objectives in choosing which attributes to display together. The first objective is to understand the correlation of one attribute to another, and most commonly, of a given attribute to the original seismic amplitude data. The second objective is to visualize the confidence or relevance of a given attribute by modulating it with a second attribute. The third objective is to provide a more integrated image of the seismic data volume by choosing attributes that are mathematically independent but correlated through the underlying geology. I developed the interpretation value of the HLS display technique on a 3D data volume acquired over the Central Basin Platform of west Texas exhibiting faults, fractures, folds, channels, pinch outs, and karst features. To be a useful “technique,” I need to demonstrate these workflows within a specific package. Although I implemented the workflow in Petrel 2014, similar images can be generated using any software with flexible opacity capabilities. I also developed a short list of attribute combinations that are particularly amenable to corendering in HLS.

Pitfalls and limitations in seismic attribute interpretation of tectonic features

Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small processing and velocity errors in seismic imaging. As a result, the chance that an interpreter will suffer a pitfall is inversely proportional to his or her experience. Interpreters with a history of making conventional maps from vertical seismic sections will have previously encountered problems associated with acquisition, processing, and imaging. Because they know that attributes are a direct measure of the seismic amplitude data, they are not surprised that such attributes “accurately” represent these familiar errors. Less experienced interpreters may encounter these errors for the first time. Regardless of their level of experience, all interpreters are faced with increasingly larger seismic data volumes in which seismic attributes become valuable tools that aid in mapping and communicating geologic features of interest to their colleagues. In terms of attributes, structural pitfalls fall into two general categories: false structures due to seismic noise and processing errors including velocity pull-up/push-down due to lateral variations in the overburden and errors made in attribute computation by not accounting for structural dip. We evaluate these errors using 3D data volumes and find areas where present-day attributes do not provide the images we want.

Relatively short-term correlation among deformation, degassing, and seismicity: a case study from Concepción volcano, Nicaragua

Concepcion is a frequently active composite volcano in Nicaragua, and is located on Ometepe Island, within Lake Nicaragua. Significant eruptive activity took place at this volcano between March and May 2010, consisting of ash and gas explosions (VEI 1-2). We compare geodetic baseline changes observed with global positioning system (GPS), sulfur dioxide flux (SO2), and seismic amplitude (SAM) data collected at Concepcion during April - June, 2010, and February - April, 2011. Time series analysis reveals a remarkable correlation among the data sets during 2010, when the volcano was erupting. In contrast, the volcano was at its background level of activity in 2011 and the statistical correlation among the time series is not significant for this period. We explain the emergence of correlation among the time series during eruptive activity through modeling of the GPS data with emplacement of a magma column in an open conduit. In the model, magma rose in the conduit, between May 5 and 14, 2010, from a shallow reservoir located at similar to 1.8 km depth. Later, between May 24 and 31, 2010, the top of the magma column descended to almost 600m depth, corresponding to the cessation of eruptive activity. Thus, cross-correlation and an integrated analysis of these geophysical time series on a timescale of days helps to reveal the dynamics of the magma plumbing system operating below Concepcion volcano.

Applying a new synchronous inversion of seismograms using maximum likelihood method and stochastic refinements to study ultra-thin oil-saturated reservoirs

Seismic inversion makes use of single or multi-dimensional seismic trace data to derive elastic properties from seismic amplitude data. These elastic properties are subsequently used to make inferences about seismic lithology, lithologic properties, and the presence of fluids. Most implementations of seismic inversions operate on limited stacked subsets of the seismic data. Common inputs to inversion methods include angle stacks, offset stacks, or multiple stacks of time-lapsed data. The implementation in this paper makes use of a synchronous pre-stack inversion based on the maximum likelihood algorithm (Anat Canning and Alex Malkin, 2009). The PMLI inversion is applicable to time and depth angle or offset seismograms. It is a full pre-stack inversion, which inverts each and every trace of an offset or angle gather and returns elastic properties. The PMLI inversion can also invert partial angular or offset sums, which can be created in any processing system. As a complete pre-stack inversion, PMLI provides higher accuracy and noise immunity as observed in the output results of Pw and Sw impedances, density, Vp/Vs, Poisson’s ratio, Lambda Rho (LR) and Mu Rho (MR). PMLI also incorporates a necessary and effective preprocessing step, which is performed on-the-fly as part of the inversion process. Because the PMLI method operates on gathers, it is easily and efficiently parallelized for multi-core and multi-node clusters and for shared memory architectures.

Introduction to the special section on seismic-amplitude data and well logs

Reservoir description and production forecast are customarily accomplished by combining well logs, core laboratory data, and fluid-production measurements acquired in multiple wells with spatial-interpolation methods. The greatest and most diverse petrophysical, fluid, and compositional information is invariably concentrated at well locations within reservoir depth intervals. Spatial interpolation and extrapolation of that information between and beyond existing well locations are necessary for infill and step-out drilling, to anticipate fluid displacement caused by primary and/or enhanced recovery processes, and generally to maximize hydrocarbon production.

Joint stochastic inversion of 3D prestack seismic-amplitude data and well logs for high-resolution reservoir characterization of deepwater hydrocarbon reservoirs

A new algorithm for joint stochastic inversion of well logs and multiple-angle stacks of migrated 3D prestack seismic data is based on a Bayesian statistical search criterion implemented with fast Markov-chain Monte Carlo updates. It enforces a priori measures of spatial correlation as well as geometric structural and stratigraphic embedding. Results consist of spatial distributions of elastic properties with a vertical resolution intermediate between that of seismic-amplitude data and well logs. In addition, the algorithm provides quantitative estimates of nonuniqueness based on statistical distribution of multiple spatial realizations derived from random initial models. It is also possible to estimate lithology and petrophysical properties such as porosity by enforcing multidimensional statistical correlations between elastic and petrophysical properties sampled from well logs. Results are described from the successful application of the inversion algorithm to the high-resolution characterization of hydrocarbon-producing units of a deepwater reservoir in the central Gulf of Mexico. Sensitivity analyses of resolution and non-uniqueness at blind-well locations corroborate the reliable estimation of elastic and petrophysical properties. Estimated distributions of lithology and elastic properties are influenced only marginally by the choice of inversion parameters and the assumed measures of spatial correlation.

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

This letter presents ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> , a new computationally efficient ant-colony-optimization-based algorithm, tailored for continuous-domain problems. The ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> algorithm is well suited for application in seismic inversion problems, owing to its intrinsic features, such as heuristics in generating the initial solution population and its facility to deal with multiobjective optimization problems. Here, we show how the ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> algorithm can be applied in two methodologies to obtain 3-D impedance maps from poststack seismic amplitude data. The first methodology pertains to the traditional method of forward convolution of a reflectivity model with the estimated wavelet, where ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> is used to guess the appropriate wavelet as the reflectivity model. In the second methodology, we propose an even faster inversion algorithm based on inverse filter optimization, where ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> optimizes the inverse filter that is deconvolved with the seismic traces and results in a reflectivity model similar to that found in well logs. This modeled inverse filter is then deconvolved with the entire 3-D seismic volume. In experiments, both the methodologies are applied to a synthetic 3-D seismic volume. The results validate their feasibility and the suitability of ACO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\BBR</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> as an optimization algorithm. The results also show that the second methodology has the advantages of a much higher convergence speed and effectiveness as a seismic inversion tool.

Resolving subtle stratigraphic features using spectral ridges and phase residues

Seismic interpretation is dependent on the quality and resolution of seismic data. Unfortunately, seismic amplitude data are often insufficient for detailed sequence stratigraphy interpretation. We reviewed a method to derive high-resolution seismic attributes based upon complex continuous wavelet transform pseudodeconvolution (PD) and phase-residue techniques. The PD method is based upon an assumption of a blocky earth model that allowed us to increase the frequency content of seismic data that, for our data, better matched the well log control. The phase-residue technique allowed us to extract information not only from thin layers but also from interference patterns such as unconformities from the seismic amplitude data. Using data from a West Texas carbonate environment, we found out how PD can be used not only to improve the seismic well ties but also to provide sharper sequence terminations. Using data from an Anadarko Basin clastic environment, we discovered how phase residues delineate incised valleys seen on the well logs that are difficult to see on vertical slices through the original seismic amplitude.

Fault and fracture distribution within a tight-gas sandstone reservoir: Mesaverde Group, Mamm Creek Field, Piceance Basin, Colorado, USA

The distribution and orientation of faults, fracture intensity and seismic-reflection characteristics of the Mesaverde Group (Williams Fork and Iles formations) at Mamm Creek Field vary stratigraphically, and with lithology and depositional setting. For the Mesaverde Group, the occurrence of faults and natural fractures is important as they provide conduits for gas migration, and enhance the permeability and productivity of the tight-gas sandstones. The Upper Cretaceous Mesaverde Group represents fluvial, alluvial-plain, coastal-plain and shallow-marine depositional environments. Structural interpretations based on three-dimensional (3D) seismic-amplitude data, ant-track (algorithm that enhances seismic discontinuities) seismic attributes and curvature attributes are utilized jointly to understand the complex fault characteristics of the Williams Fork Formation. This study reveals that the lowermost lower Williams Fork Formation is characterized by NNW- and east–west-trending small-scale thrust and normal faults. Study suggests that the uppermost lower Williams Fork Formation, and the middle and upper Williams Fork formations, exhibit NNE- and east–west-trending arrays of fault splays that terminate upwards and do not appear to displace the upper Williams Fork Formation. In the uppermost Williams Fork Formation and Ohio Creek Member, NNE-trending discontinuities are displaced by east–west-trending events and the east–west-trending events dominate. Fracture analysis, based on borehole-image logs, together with ant-track and attenuation-related seismic attributes, illustrates the spatial variability of fracture intensity and lithological controls on fracture distribution. In general, higher fracture intensity occurs within the southern, southwestern and western portions of the field, and fracture intensity is greater within the fluvial sandstone deposits of the middle and upper Williams Fork formations. More than 90% of natural fractures occur in sandstones and siltstones. In situ stress analysis, based on induced-tensile fractures and borehole breakouts, indicates a NNW orientation of present-day maximum horizontal stress ( S H max ), an approximate 20° rotation (in a clockwise direction) in the orientation of S H max with depth and an abrupt stress shift below the Williams Fork Formation within the Rollins Sandstone Member.

Azimuthal reflectivity inversion

Seismic fracture prediction is becoming a more important exploration and development problem with the growing focus on unconventional reservoirs. A non-linear inversion technique is presented to estimate layer-based fracture parameters and velocities based on azimuthal reflectivity data. The earth model assumes a single set of vertical fractures per layer parameterized in terms of linear slip parameters - the normal and tangential fracture weaknesses - and fracture strike. In addition, the background P-wave and S-wave impedances are estimated. Either the exact Zoeppritz equation or some linearization thereof is used in a convolutional modelling scheme to estimate seismic amplitude data. The inverse problem is solved in a nonlinear fashion using simulated annealing. The new technique has several advantages over performing azimuthal amplitude versus angle analysis (AVAz). The reflectivity calculation used in the new technique is more theoretically correct, allowing for the symmetry plane to change as a function of layer. The 90 degree ambiguity in estimating the symmetry plane typical of the near offset approximation also disappears. Further, there is an improvement in the isotropic parameter estimates compared to isotropic inversion since the bias introduced by neglecting anisotropy has been removed by incorporating it into the forward model. The azimuthal inversion is demonstrated on both synthetic and real seismic data.

Time-lapse surface seismic inversion with thin bed resolution for monitoring CO2 sequestration: A case study from Cranfield, Mississippi

The feasibility of carbon dioxide sequestration research at Cranfield, Mississippi is studied by injecting millions tonnes of CO2 into the lower Tuscaloosa sandstone Formation over a two year period. Time-lapse surface seismic surveys were recorded at pre-(2007) and post-(2010) injection stages to monitor the subsurface fluid plume. The injection interval, appearing as a thin layer in the well-log data, shows very weak signature of CO2 injection in the time-lapse seismic amplitude data. In order to improve the capability of tracking CO2 plume movement using seismic data, we have applied a basis pursuit inversion (BPI) method to the post-stack seismic datasets. This method of inversion incorporates a priori information as a wedge dictionary and employs a L1-norm optimization for obtaining solutions with improved resolution. The inverted time-lapse acoustic impedances show a strongly decreasing trend mostly at the top of the injection interval, which is in agreement with well-log measurements for CO2 saturation. Improved resolution time-lapse impedance mapping therefore is an effective tool for imaging the displacement of the CO2 plume.

Estimation of near-surface quality factors by constrained inversion of Rayleigh-wave attenuation coefficients

Quality factors (Q) of near-surface materials are as important as velocities of the materials in many applications. Only phase information of surface-wave data is utilized when high-frequency (≥ 2 Hz) surface-wave data are routinely inverted to determine near-surface shear (S)-wave velocities. Amplitude information of high-frequency surface-wave data can be used to determine quality factors of near-surface materials. Given S-wave velocity, compressional (P)-wave velocity, and Rayleigh-wave phase velocities , it is feasible to solve for S-wave quality factor Q S and P-wave quality factor Q P (for some specific velocity models) down to 30 m below the ground surface in many settings by inverting high-frequency Rayleigh-wave attenuation coefficients in a layered earth model. Amplitude of seismic data is an exponential function of attenuation coefficients. When calculating attenuation coefficients from changes in amplitude, this nonlinear nature would result in that small variations in amplitude cause huge changes in attenuation coefficients. This result suggests data (attenuation coefficients) that normally possess large errors could eventually transfer to a model (quality factors); therefore, constraints (or a priori information) on models are necessary. Because an inversion system to solve this problem is unstable, a regularization parameter must be introduced into an inversion algorithm to stabilize the inversion. These characteristics of the inversion problem allow us to solve the problem as a constrained and regularized linear system . Usually, a set of models that meet the defined constraints can be obtained by solving the system. Based on the linear nature of the inversion system, a smooth model can be selected from the set of models as a solution of the inversion using the L-curve method. This approach is a trade-off solution between data misfit and model length. Several real-world examples demonstrate the importance of constraints in finding acceptable realistic quality factors from empirical data. ► Amplitude of seismic data is an exponential function of attenuation coefficients. ► Small variations in amplitude cause huge changes in attenuation coefficients. ► Large errors in attenuation coefficients could transfer to quality factors. ► Constraints (or a priori information) on models are necessary. ► A realistic model can be selected using the L-curve method.

Seismic attributes and structural interpretation—it takes two to tango...

In this paper, different 3D seismic attributes calculated to improve the accuracy and robustness of structural interpretations in several energy-rich Australian basins are compared. Detailed and precise fault and fracture maps are crucial not only for initial petroleum play assessment, but also for fault seal analysis and reservoir integrity studies. Robust fault and fracture models are also needed to improve the design of reservoir simulation programs and to manage the long-term containment of gas in geological formations. Different attributes (including coherency, dip-steered similarity, dip-steered median filter, dip-steered variance, apparent dip, and dip-steered most-positive and most-negative curvatures) from an array of 3D seismic datasets to better image structural fabrics, such as normal and different fractures patterns, in the North Perth, Cooper, Ceduna, Otway and Gippsland basins have been calculated. The results provide a remarkable improvement in the quality and precision of structural maps using this multi-attribute mapping workflow by comparison with more conventional maps produced, solely using seismic amplitude data. The key to the successful application of multi-attribute structural analysis, however, remains with the ability of the interpreter to identify meaningful structural information from a large volume of data. Thus, the structural expertise of the interpreter remains as the cornerstone to making geological sense of the various seismic processing techniques available.

Application of Fault Detection Using Ant-Tracking Algorithm: Daqing Oilfield Example

The traditional manual fault interpretation is time consuming. A powerful method for rapidly obtaining detailed fault and fracture interpretation from seismic amplitude data was proposed. It can remarkably save time during the fault interpretation task. Moreover, it can easily detect some minor faults that can not be traced manually. This method has been applied to one of Chinese oil reservoirs. The resulting interpretation, in conjunction with fracture information derived from well log measurements are illustrated.

Rock physics-based seismic trace analysis of unconsolidated sediments containing gas hydrate and free gas in Green Canyon 955, Northern Gulf of Mexico

The gas hydrate petroleum system at the 2009 Gulf of Mexico Gas Hydrate Joint Industry Project Leg II (JIP Leg II) Green Canyon 955 (GC955) site shows a complex seismic amplitude and waveform response of highly negative and positive amplitudes with continuous and discontinuous character within inferred gas-hydrate- and gas-bearing sand reservoirs. Logging-while-drilling (LWD) data obtained during JIP Leg II and conventional 3-D seismic data allowed for the identification of thick highly concentrated hydrate layers by integrating rock physics modeling, amplitude and thin layer analysis, and spectral decomposition. Rock physics modeling with constraints from three JIP LWD holes allowed for the analysis of variations in acoustic amplitude characteristics as a product of hydrate saturation, gas saturation, and reservoir thickness. Using the well log-derived acoustic models, thick highly concentrated gas hydrate with and without underlying free gas accumulations have been identified. These results suggest that thick highly concentrated gas-hydrate-bearing sand units (with thicknesses greater than half of the seismic tuning thickness and gas hydrate saturations greater than 50%) underlain by gas can be differentiated from sands containing only gas, but thin gas-hydrate-bearing sand units with low gas hydrate concentrations (with thicknesses less than half of the seismic tuning thickness and gas hydrate saturations less than 50%) are difficult to identify from post-stack seismic amplitude data alone. Within GC955, we have identified six zones with seismic amplitude anomalies interpreted as being caused by gas hydrate deposits with variable lateral extent, thickness and saturation, and in some cases overlying free-gas-bearing intervals. Synthetic seismic images produced from well-log- and model-derived velocity and density distributions mimic similar reflection characteristics in the corresponding field seismic data.