Acquisition of small surgical 3D seismic surveys in urban areas within the Fort Worth Basin

Thomas D. Bowman; Wayne “Woody” Woodside; Steve Culpepper

doi:10.1190/1.2542447

Rapid acquisition of small 3D seismic surveys: Urban areas within the Fort Worth basin

10.1190/1.2370303 ◽

2006 ◽

Author(s):

Thomas D. Bowman ◽

Mark Russell ◽

Wayne “Woody” Woodside ◽

Steve Culpepper

Keyword(s):

Urban Areas ◽

Fort Worth ◽

3D Seismic ◽

Seismic Surveys ◽

Fort Worth Basin ◽

Rapid Acquisition

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A window into the Proterozoic: Integrating 3D seismic, gravity, and magnetic data to image subbasement structures in the southeast Fort Worth basin

Interpretation ◽

10.1190/int-2013-0041.1 ◽

2013 ◽

Vol 1 (2) ◽

pp. T125-T141 ◽

Cited By ~ 18

Author(s):

Murari Khatiwada ◽

G. Randy Keller ◽

Kurt J. Marfurt

Keyword(s):

Seismic Survey ◽

Magnetic Data ◽

Gravity Modeling ◽

Barnett Shale ◽

Fort Worth ◽

3D Seismic ◽

Lower Paleozoic ◽

Seismic Surveys ◽

Fort Worth Basin ◽

Basement Structures

The Fort Worth basin (FWB) is one of the most fully developed shale gas fields in North America. Although there are hundreds of drilled wells in the basin, almost none of them reach the Precambrian basement. Imaged by perhaps 100 3D seismic surveys, the focus on the relatively shallow, flat-lying Barnett Shale objective has resulted in little published work on the basement structures underlying the Lower Paleozoic strata. Subtle folds and systems of large joints are present in almost all 3D seismic surveys in the FWB. At the Cambro-Ordovician Ellenburger level, these joints are often diagenetically altered and exhibit collapse features at their intersections. We discovered how the basement structures relate to overlying Paleozoic reservoirs in the Barnett Shale and Ellenburger Group. In support of our investigation, the Marathon Oil Company provided a high-quality, wide-azimuth, 3D seismic data near the southeast fringe of the FWB. In addition to the seismic volume, we integrated the seismic results with gravity, magnetic, well log, and geospatial data to understand the basement and subbasement structures in the southeast FWB. Major tectonic features including the Ouachita frontal thrust belt, Lampasas arch, Llano uplift, and Bend arch surround the southeast FWB. Euler deconvolution and integrated forward gravity modeling helped us extend our interpretation beyond the 3D seismic survey into a regional context.

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Applying 3D Seismic Technology to Better Understand the Mechanical Variability of the Lower Barnett Shale in Southern Montague and Northern Wise Counties, Fort Worth Basin.

10.1190/urtec2013-033 ◽

2013 ◽

Author(s):

Andy Stephens

Keyword(s):

Barnett Shale ◽

Fort Worth ◽

3D Seismic ◽

Fort Worth Basin

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Porosity estimation in the Fort Worth Basin constrained by 3D seismic attributes integrated in a sequential Bayesian simulation framework

Geophysics ◽

10.1190/geo2016-0506.1 ◽

2017 ◽

Vol 82 (4) ◽

pp. M67-M80 ◽

Cited By ~ 4

Author(s):

Martin Blouin ◽

Mickaele Le Ravalec ◽

Erwan Gloaguen ◽

Mathilde Adelinet

Keyword(s):

Oil And Gas ◽

Reservoir Characterization ◽

Geophysical Methods ◽

Seismic Attributes ◽

Seismic Inversion ◽

Fort Worth ◽

3D Seismic ◽

Reservoir Properties ◽

Fort Worth Basin ◽

Porosity Estimation

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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