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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.
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.
Shallow-water carbonate structures are characterized by different shapes, sizes and identifying features, which depend, among other factors, on the age of deposition and on the carbonate factory associated with a specific geologic period. These variations have a significant impact on the imaging of these structures in reflection seismic data. This study aims at providing an overall, albeit incomplete, picture of how the seismic expression of shallow-water carbonate structures has evolved through deep time. 297 shallow-water carbonate systems of different ages, spanning from Precambrian to present, with a worldwide distribution of 159 sedimentary basins, have been studied. For each epoch, representative seismic examples of shallow-water carbonate structures were described through the assessment of a selection of discriminating seismic criteria, or parameters. The thinnest structures, commonly represented by ramp systems, usually occurred after mass extinction events, and are mainly recognizable in seismic data through prograding clinoform reflectors. The main diagnostic seismic features of most of the thickest structures, which were found to be Precambrian, Late Devonian, Middle-Late Triassic, Middle-Late Jurassic, some Early Cretaceous pre-salt systems, #8220;middle#8221; and Late Cretaceous, Middle-Late Miocene and Plio-Pleistocene, are steep slopes, and reefal facies. Slope-basinal, resedimented seismic facies, were mostly observed in thick, steep-slope platforms, and they are more common, except for megabreccias, in post-Triassic structures. Seismic-scale, early karst-related dissolution features were mostly observed in icehouse, platform deposits. Pinnacle structures and the thickest margin rims are concentrated in a few epochs, such as Middle-Late Silurian, Middle-Late Devonian, earliest Permian, Late Triassic, Late Jurassic, Late Paleocene, Middle-Upper Miocene, and Plio-Pleistocene, which are all characterized by high-efficiency reef builders.
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