Dengliang Gao

Latest developments in seismic texture analysis for subsurface structure, facies, and reservoir characterization: A review

In exploration geology and geophysics, seismic texture is still a developing concept that has not been sufficiently known, although quite a number of different algorithms have been published in the literature. This paper provides a review of the seismic texture concepts and methodologies, focusing on latest developments in seismic amplitude texture analysis, with particular reference to the gray level co-occurrence matrix (GLCM) and the texture model regression (TMR) methods. The GLCM method evaluates spatial arrangements of amplitude samples within an analysis window using a matrix (a two-dimensional histogram) of amplitude co-occurrence. The matrix is then transformed into a suite of texture attributes, such as homogeneity, contrast, and randomness, which provide the basis for seismic facies classification. The TMR method uses a texture model as reference to discriminate among seismic features based on a linear, least-squares regression analysis between the model and the data within an analysis window. ...

Application of three-dimensional seismic texture analysis with special reference to deep-marine facies discrimination and interpretation: Offshore Angola, west Africa

In seismic stratigraphy, a seismic texture is an acoustic expression of the stratigraphic configuration of beds and thin beds that is related to depositional facies and reservoir properties. This study applies an amplitude co-occurrence matrix method to characterize seismic textures in a deep-marine setting offshore Angola (west Africa). Beginning with high-quality three-dimensional seismic data, the algorithm calculates textural homogeneity, contrast, and randomness by evaluating the amplitude co-occurrence matrix of a texture element at each sample location. Based on textural homogeneity, contrast, and randomness, a clustering analysis segments the regular seismic amplitude volume into different categories in a resulting thematic texture class volume. An integrated interpretation of the texture classes and regular amplitude characters, along with contemporary and outcrop analogs of deep-water systems, leads to the identification of several major facies elements such as channel fill, levee, overbank, mass-transport complex, and marine shale in the lower Miocene–upper Pliocene stratigraphic interval. Sequential stratigraphic horizon slicing through the texture class volume indicates that the geomorphology and facies architecture have changed significantly from the early Miocene to the late Pliocene, which is instrumental in analyzing sequence stratigraphy, delineating the play fairway, and evaluating hydrocarbon potential. Subvolume detection of distinct texture classes shows that different facies bodies are complex in extent, geometry, and connectivity in three dimensions, which provide critical seismic-scale constraints for geologically meaningful reservoir modeling and simulation.

Texture model regression for effective feature discrimination: Application to seismic facies visualization and interpretation

The classical approach to feature discrimination requires extraction and classification of multiple attributes. Such an approach is expensive in terms of computational time and storage space, and the results are generally difficult to interpret. With increasing data size and dimensionality, along with demand for high performance and productivity, the effectiveness of a feature‐discrimination methodology has become a critically important issue in many areas of science. To address such an issue, I developed a texture model regression (TMR) methodology. Unlike classical attribute extraction and classification algorithms, the TMR methodology uses an interpreter‐defined texture model as a calibrating filter and regresses the model texture with the data texture at each sample location to create a regression‐gradient volume. The new approach not only dramatically reduces computational cycle time and space but also creates betters results than those obtained from classical techniques, resulting in improved featur...

3D seismic volume visualization and interpretation: An integrated workflow with case studies

One of the major problems in subsurface seismic exploration is the uncertainty (nonuniqueness) in geologic interpretation because of the complexity of subsurface geology and the limited dimension of the data available. Case studies from worldwide exploration projects indicate that an integrated, three-dimensional (3D) seismic volume visualization and interpretation workflow contributes to resolving the problem by mining and exposing critical geologic information from within seismic data volumes. Following 3D seismic data acquisition and processing, the interpretation workflow consists of four integrated phases from data selection and conditioning, to structure and facies characterization, to prospect evaluation and generation, to well-bore planning. In the data selection and conditioning phase, the most favored and frequently used data are the full-angle, limited-angle, and limited-azimuth stack amplitude with significant structure and facies enhancements. Signal-to-noise ratio, color scheme, dynamic rang...

Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement

In a 3D seismic survey, detecting seismic discontinuities is vital to robust structural and stratigraphic analysis in the subsurface. Previous methods have difficulty highlighting subtle discontinuities from seismic data in cases where the local amplitude variation is of non-zero mean. This study proposes implementing a gray-level transformation and the Canny edge detector for improved imaging of discontinuities. Specifically, the new process transforms seismic signals to be of zero mean and helps amplify subtle discontinuities, leading to an enhanced visualization for structural and stratigraphic details. Applications to various 3D seismic datasets demonstrate that the new algorithm helps better define channels, faults, and fractures than the traditional similarity, amplitude gradient, and semblance attributes. An improved algorithm for extracting 3D seismic discontinuity attribute.Gray-level transformation helps re-characterize subtle seismic features.Implementing Canny edge detector for efficient discontinuity detection.Integrating discontinuity magnitude and azimuth for fracture characterization.

A new algorithm for evaluating 3D curvature and curvature gradient for improved fracture detection

In 3D seismic interpretation, both curvature and curvature gradient are useful seismic attributes for structure characterization and fault detection in the subsurface. However, the existing algorithms are computationally intensive and limited by the lateral resolution for steeply-dipping formations. This study presents new and robust volume-based algorithms that evaluate both curvature and curvature gradient attributes more accurately and effectively. The algorithms first instantaneously fit a local surface to seismic data and then compute attributes using the spatial derivatives of the built surface. Specifically, the curvature algorithm constructs a quadratic surface by using a rectangle 9-node grid cell, whereas the curvature gradient algorithm builds a cubic surface by using a diamond 13-node grid cell. A dip-steering approach based on 3D complex seismic trace analysis is implemented to enhance the accuracy of surface construction and to reduce computational time. Applications to two 3D seismic surveys demonstrate the accuracy and efficiency of the new curvature and curvature gradient algorithms for characterizing faults and fractures in fractured reservoirs. Robust algorithms for generating 3D curvature and curvature gradient attribute.Automatic surface construction improves computational accuracy.Implementing 3D complex seismic trace analysis for efficient dip estimates.

Along-axis segmentation and growth history of the Rome trough in the Central Appalachian Basin

The Rome trough, a northeast-trending graben, is that part of the Cambrian interior rift system that extends into the central Appalachian foreland basin in eastern North America. On the basis of changes in graben polarity and rock thickness shown from exploration and production wells, seismic lines, and gravity and magnetic intensity maps, we divide the trough into the eastern Kentucky, southern West Virginia, and northern West Virginia segments. In eastern Kentucky, the master synthetic fault zone consists of several major faults on the northwestern side of the trough where the most significant thickness and facies changes occur. In southern West Virginia, however, a single master synthetic fault, called the East-Margin fault, is located on the southeastern side of the trough. Syndepositional motion along that fault controlled the concentrated deposition of both the rift and postrift sequences. The East-Margin fault continues northward into the northern West Virginia segment, apparently with less stratigraphic effect on postrift sequences, and a second major normal fault, the Interior fault, developed in the northern West Virginia segment. These three rift segments are separated by two basement structures interpreted as two accommodation zones extending approximately along the 38th parallel and Burning-Mann lineaments. Computer-aided interpretation of seismic data and subsurface geologic mapping indicate that the Rome trough experienced several major phases of deformation throughout the Paleozoic. From the Early(?)-Middle Cambrian (pre-Copper Ridge deposition), rapid extension and rifting occurred in association with the opening of the Iapetus-Theic Ocean at the continental margin. The Late Cambrian-Middle Ordovician phase (Copper Ridge to Black River deposition) was dominated by slow differential subsidence, forming a successor sag basin that may have been caused by postrift thermal contraction on the passive continental margin. Faults of the Rome trough were less active from the Late Ordovician-Pennsylvanian (post-Trenton deposition), but low-relief inversion structures began to form as the Appalachian foreland started to develop. These three major phases of deformation are speculated to be responsible for the vertical stacking of different structural styles and depositional sequences that may have affected potential reservoir facies, trapping geometry, and hydrocarbon accumulation.

3D Seismic Flexure Analysis for Subsurface Fault Detection and Fracture Characterization

Seismic flexure is a new geometric attribute with the potential of delineating subtle faults and fractures from three-dimensional (3D) seismic surveys, especially those overlooked by the popular discontinuity and curvature attributes. Although the concept of flexure and its related algorithms have been published in the literature, the attribute has not been sufficiently applied to subsurface fault detection and fracture characterization. This paper provides a comprehensive study of the flexure attribute, including its definition, computation, as well as geologic implications for evaluating the fundamental fracture properties that are essential to fracture characterization and network modeling in the subsurface, through applications to the fractured reservoir at Teapot Dome, Wyoming (USA). Specifically, flexure measures the third-order variation of the geometry of a seismic reflector and is dependent on the measuring direction in 3D space; among all possible directions, flexure is considered most useful when extracted perpendicular to the orientation of dominant deformation; and flexure offers new insights into qualitative/quantitative fracture characterization, with its magnitude indicating the intensity of faulting and fracturing, its azimuth defining the orientation of most-likely fracture trends, and its sign differentiating the sense of displacement of faults and fractures.

Application of seismic texture model regression to seismic facies characterization and interpretation

This paper applies a texture model regression method to characterize seismic facies with particular reference to frontier, deep marine depositional settings. The algorithm introduces and designs a seismic texture model in an adaptive manner in terms of dimensionality, size, amplitude, frequency, and phase using mathematical, synthetic, or actual seismic data. The model serves as a reference for seismic feature discrimination by comparing actual seismic texture at each location with the model through a linear, least-squares regression analysis.

3-D VCM seismic textures: A new technology to quantify seismic interpretation

Summary The author proposes and employs volume textures extracted using a Voxel Co-occurrence Matrix (VCM), here called the “VCM Seismic Textures”, to quantify interpretation of seismic data from a 3-D perspective. On the basis of the VCM seismic textures, the author developed a new process of translating a seismic amplitude volume into a seismic facies classification (thematic) volume. Correlation between the seismic amplitude volume with the VCM seismic texture volumes and the seismic facies classification volume indicates that VCM seismic textures are able to capture major seismic facies. Case studies show that not only are the facies classification results using the VCM seismic textures consistent with large-scale geological facies models, but also the results reveal additional details that are difficult to identify using conventional seismic interpretation technologies. Thus, the VCM seismic texture analysis may provide a new and important basis for quantitative seismic interpretation and hydrocarbon exploration.