Karst related vertical collapse structure and related lineament detection by seismic attributes on Fort Worth basin seismic data volume

2003 ◽  
Author(s):  
Srinivasa Prasad Jyosyula ◽  
Kurt J. Marfurt ◽  
E. Charlotte Sullivan
2018 ◽  
Vol 6 (2) ◽  
pp. T349-T365 ◽  
Author(s):  
Xuan Qi ◽  
Kurt Marfurt

One of the key tasks of a seismic interpreter is to map lateral changes in surfaces, not only including faults, folds, and flexures, but also incisements, diapirism, and dissolution features. Volumetrically, coherence provides rapid visualization of faults and curvature provides rapid visualization of folds and flexures. Aberrancy measures the lateral change (or gradient) of curvature along a picked or inferred surface. Aberrancy complements curvature and coherence. In normally faulted terrains, the aberrancy anomaly will track the coherence anomaly and fall between the most positive curvature anomaly defining the footwall and the most negative curvature anomaly defining the hanging wall. Aberrancy can delineate faults whose throw falls below the seismic resolution or is distributed across a suite of smaller conjugate faults that do not exhibit a coherence anomaly. Previously limited to horizon computations, we extend aberrancy to uninterpreted seismic data volumes. We apply our volumetric aberrancy calculation to a data volume acquired over the Barnett Shale gas reservoir of the Fort Worth Basin, Texas. In this area, the Barnett Shale is bound on the top by the Marble Falls Limestone and on the bottom by the Ellenburger Dolomite. Basement faulting controls karstification in the Ellenburger, resulting in the well-known “string of pearls” pattern seen on coherence images. Aberrancy delineates small karst features, which are, in many places, too smoothly varying to be detected by coherence. Equally important, aberrancy provides the azimuthal orientation of the fault and flexure anomalies.


Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. P41-P51 ◽  
Author(s):  
Saleh Al-Dossary ◽  
Kurt J. Marfurt

One of the most accepted geologic models is the relation between reflector curvature and the presence of open and closed fractures. Such fractures, as well as other small discontinuities, are relatively small and below the imaging range of conventional seismic data. Depending on the tectonic regime, structural geologists link open fractures to either Gaussian curvature or to curvature in the dip or strike directions. Reflector curvature is fractal in nature, with different tectonic and lithologic effects being illuminated at the [Formula: see text] and [Formula: see text] scales. Until now, such curvature estimates have been limited to the analysis of picked horizons. We have developed what we feel to be the first volumetric spectral estimates of reflector curvature. We find that the most positive and negative curvatures are the most valuable in the conventional mapping of lineations — including faults, folds, and flexures. Curvature is mathematically independent of, and interpretatively complementary to, the well-established coherence geometric attribute. We find the long spectral wavelength curvature estimates to be of particular value in extracting subtle, broad features in the seismic data such as folds, flexures, collapse features, fault drags, and under- and overmigrated fault terminations. We illustrate the value of these spectral curvature estimates and compare them to other attributes through application to two land data sets — a salt dome from the onshore Louisiana Gulf Coast and a fractured/karsted data volume from Fort Worth basin of North Texas.


Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. B157-B168 ◽  
Author(s):  
Olubunmi O. Elebiju ◽  
G. Randy Keller ◽  
Kurt J. Marfurt

Effective hydraulic fracturing is critical for generating permeability within the Barnett Shale of the Fort Worth basin (FWB). Therefore, knowledge of the nature of the induced and natural fractures, faults, and collapse features that may form conduits to the underlying Ellenburger aquifer is vital. We use coherence and curvature seismic attributes, which are sensitive to faults, fractures, and collapse features, to map sedimentary features. We then integrate high-resolution aeromagnetic (HRAM) data with the seismic attributes extracted along the Ellenburger Formation and the top of basement from the north-central portion of the FWB, thereby linking features in the Precambrian basement to shallower sedimentary structures. HRAM-derived maps, designed to enhance basement structures, confirm that much of the sedimentary faulting is basement controlled. Specifically, attribute lineaments are aligned parallel to HRAM anomaly lineaments, consistent with regional tectonics. The northeast-southwest and northwest-southeast orientations of folds and faults in the sedimentary section parallel the northeast-trending Ouachita orogenic belt and the northwest-trending Muenster arch, which in turn correlate with reactivated Cambrian/late Precambrian basement faults. Mapping such features can aid in the design of the hydraulic fracture program and ability to predict structurally deformed areas of the basin.


2016 ◽  
Vol 4 (2) ◽  
pp. SG1-SG9 ◽  
Author(s):  
Marcus P. Cahoj ◽  
Sumit Verma ◽  
Bryce Hutchinson ◽  
Kurt J. Marfurt

The term acquisition footprint is commonly used to define patterns in seismic time and horizon slices that are closely correlated to the acquisition geometry. Seismic attributes often exacerbate footprint artifacts and may pose pitfalls to the less experienced interpreter. Although removal of the acquisition footprint is the focus of considerable research, the sources of such artifact acquisition footprint are less commonly discussed or illustrated. Based on real data examples, we have hypothesized possible causes of footprint occurrence and created them through synthetic prestack modeling. Then, we processed these models using the same workflows used for the real data. Computation of geometric attributes from the migrated synthetics found the same footprint artifacts as the real data. These models showed that acquisition footprint could be caused by residual ground roll, inaccurate velocities, and far-offset migration stretch. With this understanding, we have examined the real seismic data volume and found that the key cause of acquisition footprint was inaccurate velocity analysis.


Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 368-376 ◽  
Author(s):  
Bruce S. Hart ◽  
Robert S. Balch

Much industry interest is centered on how to integrate well data and attributes derived from 3-D seismic data sets in the hope of defining reservoir properties in interwell areas. Unfortunately, the statistical underpinnings of the methods become less robust in areas where only a few wells are available, as might be the case in a new or small field. Especially in areas of limited well availability, we suggest that the physical basis of the attributes selected during the correlation procedure be validated by generating synthetic seismic sections from geologic models, then deriving attributes from the sections. We demonstrate this approach with a case study from Appleton field of southwestern Alabama. In this small field, dolomites of the Jurassic Smackover Formation produce from an anticlinal feature about 3800 m deep. We used available geologic information to generate synthetic seismic sections that showed the expected seismic response of the target formation; then we picked the relevant horizons in a 3-D seismic data volume that spanned the study area. Using multiple regression, we derived an empirical relationship between three seismic attributes of this 3-D volume and a log‐derived porosity indicator. Our choice of attributes was validated by deriving complex trace attributes from our seismic modeling results and confirming that the relationships between well properties and real‐data attributes were physically valid. Additionally, the porosity distribution predicted by the 3-D seismic data was reasonable within the context of the depositional model used for the area. Results from a new well drilled after our study validated our porosity prediction, although our structural prediction for the top of the porosity zone was erroneous. These results remind us that seismic interpretations should be viewed as works in progress which need to be updated when new data become available.


2016 ◽  
Vol 4 (2) ◽  
pp. SG19-SG29 ◽  
Author(s):  
Bo Zhang ◽  
Tengfei Lin ◽  
Shiguang Guo ◽  
Oswaldo E. Davogustto ◽  
Kurt J. Marfurt

Prestack seismic analysis provides information on rock properties, lithology, fluid content, and the orientation and intensity of anisotropy. However, such analysis demands high-quality seismic data. Unfortunately, noise is always present in seismic data even after careful processing. Noise in the prestack gathers may not only contaminate the seismic image, thereby lowering the quality of seismic interpretation, but it may also bias the seismic prestack inversion for rock properties, such as acoustic- and shear-impedance estimation. Common postmigration data conditioning includes running window median and Radon filters that are applied to the flattened common reflection point gathers. We have combined filters across the offset and azimuth with edge-preserving filters along the structure to construct a true “5D” filter that preserves amplitude, thereby preconditioning the data for subsequent quantitative analysis. We have evaluated our workflow by applying it to a prestack seismic volume acquired over the Fort Worth Basin, TX. The inverted results from the noise-suppressed prestack gathers are more laterally continuous and have higher correlation with well logs when compared with those inverted from conventional time-migrated gathers.


2015 ◽  
Vol 3 (4) ◽  
pp. SAC1-SAC7 ◽  
Author(s):  
Mathilde Adelinet ◽  
Mickaële Le Ravalec

Many geophysical studies in reservoir characterization focus on the variations in the elastic properties of rocks. They commonly involve seismic data, which are processed in terms of seismic attributes. These processed data still have to be related to the physical properties of the rock mass and the fluids saturating the pore space. This need motivated the development of research projects based upon the effective medium theory (EMT). We have used the EMT to infer porosity and also fracture data from seismic impedances in part of the Fort Worth Basin, Texas. The main idea was to take advantage of the available impedances to characterize porosity in terms of equant pores and cracks. We then focused on the volume fraction of spherical pores and crack density. Shortly thereafter, we developed an effective medium (EM) model that provided numerical responses for seismic impedances. These responses were then compared to the impedances obtained from stratigraphic inversion. The overall procedure consisted in adjusting the input parameters of the EMT model, which were the spherical porosity and the crack density, to minimize the impedance mismatch. Our case study involved two limestone formations of the Fort Worth Basin (the Marble Falls and Ellenburger Formations) and one shaly formation (the Barnett Shale). The results are promising — The EMT turns out to be a very useful tool to explain reservoir and geophysical data in terms of microstructural properties, in particular, for fractured reservoirs.


Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. M67-M80 ◽  
Author(s):  
Martin Blouin ◽  
Mickaele Le Ravalec ◽  
Erwan Gloaguen ◽  
Mathilde Adelinet

The accurate inference of reservoir properties such as porosity and permeability is crucial in reservoir characterization for oil and gas exploration and production as well as for other geologic applications. In most cases, direct measurements of those properties are done in wells that provide high vertical resolution but limited lateral coverage. To fill this gap, geophysical methods can often offer data with dense 3D coverage that can serve as proxy for the variable of interest. All the information available can then be integrated using multivariate geostatistical methods to provide stochastic or deterministic estimate of the reservoir properties. Our objective is to generate multiple scenarios of porosity at different scales, considering four formations of the Fort Worth Basin altogether and then restricting the process to the Marble Falls limestones. Under the hypothesis that a statistical relation between 3D seismic attributes and porosity can be inferred from well logs, a Bayesian sequential simulation (BSS) framework proved to be an efficient approach to infer reservoir porosity from an acoustic impedance cube. However, previous BBS approaches only took two variables upscaled at the resolution of the seismic data, which is not suitable for thin-bed reservoirs. We have developed three modified BSS algorithms that better adapt the BSS approach for unconventional reservoir petrophysical properties estimation from deterministic prestack seismic inversion. A methodology that includes a stochastic downscaling procedure is built and one that integrates two secondary downscaled constraints to the porosity estimation process. Results suggest that when working at resolution higher than surface seismic, it is better to execute the workflow for each geologic formation separately.


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