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Collaborating Authors
Results
Investigating the causes of permeability anisotropy in heterogeneous conglomeratic sandstone using multiscale digital rock
Chi, Peng (China University of Petroleum (East China), China University of Petroleum (East China)) | Sun, Jianmeng (China University of Petroleum (East China), China University of Petroleum (East China)) | Yan, Weichao (Ocean University of China, Ocean University of China) | Luo, Xin (China University of Petroleum (East China), China University of Petroleum (East China)) | Ping, Feng (Southern University of Science and Technology)
Heterogeneous conglomeratic sandstone exhibits anisotropic physical properties, rendering a comprehensive analysis of its physical processes challenging with experimental measurements. Digital rock technology provides a visual and intuitive analysis of the microphysical processes in rocks, thereby aiding in scientific inquiry. Nevertheless, the multiscale characteristics of conglomeratic sandstone cannot be fully captured by a single-scale digital rock, thus limiting its ability to characterize the pore structure. Our work introduces a proposed workflow that employs multiscale digital rock fusion to investigate permeability anisotropy in heterogeneous rock. We utilize a cycle-consistent generative adversarial network (CycleGAN) to fuse CT scans data of different resolutions, creating a large-scale, high-precision digital rock that comprehensively represents the conglomeratic sandstone pore structure. Subsequently, the digital rock is partitioned into multiple blocks, and the permeability of each block is simulated using a pore network. Finally, the total permeability of the sample is calculated by conducting an upscaling numerical simulation using the Darcy-Stokes equation. This process facilitates the analysis of the pore structure in conglomeratic sandstone and provides a step-by-step solution for permeability. From a multiscale perspective, this approach reveals that the anisotropy of permeability in conglomeratic sandstone stems from the layered distribution of grain sizes and differences in grain arrangement across different directions.
- Europe > Norway > North Sea > Central North Sea > Utsira High > PL 338 > Block 16/1 > Edvard Grieg Field > Åsgard Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > Utsira High > PL 338 > Block 16/1 > Edvard Grieg Field > Skagerrak Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > Utsira High > PL 338 > Block 16/1 > Edvard Grieg Field > Hegre Formation (0.99)
- (3 more...)
Department of Petroleum Engineering, University of Houston, 2. Metarock Laboratories, 3. Department of Earth and Atmospheric Sciences, University of Houston) 16:00-16:30 Break and Walk to Bizzell Museum 16:30-17:30 Tour: History of Science Collections, Bizzell Memorial Library, The University of Oklahoma 17:30-19:00 Networking Reception: Thurman J. White Forum Building
- North America > United States > Texas (0.51)
- North America > United States > Oklahoma (0.44)
- North America > United States > Colorado (0.31)
- Geology > Geological Subdiscipline > Geomechanics (0.76)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.49)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.48)
Petroleum Engineering, University of Houston, 2. Metarock Laboratories, 3. Department of Earth and Atmospheric Sciences, University of Houston) 16:00-16:30 Break and Walk to Bizzell Museum 16:30-17:30 Tour: History of Science Collections, Bizzell Memorial Library, The University of Oklahoma 17:30-19:00 Networking Reception: Thurman J. White Forum Building
- Research Report > New Finding (0.93)
- Overview (0.68)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Mineral (0.72)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- (2 more...)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.93)
- Well Completion > Hydraulic Fracturing (0.99)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.99)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring (0.79)
Simultaneous prediction of the geofluid and permeability of reservoirs in prestack seismic inversion
Yang, Wenqiang (Laoshan Laboratory, China University of Petroleum (East China), Pilot National Laboratory for Marine Science and Technology (Qingdao)) | Zong, Zhaoyun (Laoshan Laboratory, China University of Petroleum (East China), Pilot National Laboratory for Marine Science and Technology (Qingdao)) | Sun, Qianhao (Laoshan Laboratory, China University of Petroleum (East China), Pilot National Laboratory for Marine Science and Technology (Qingdao))
ABSTRACT Geofluid discrimination and permeability prediction are indispensable steps in reservoir evaluation. From the perspective of prestack seismic inversion, predicting fluid indicators is an effective method for obtaining fluid properties directly from seismic data. In contrast, the direct prediction of permeability from observed seismic gathers is constrained by the difficulty in establishing a link between permeability and elastic parameters. However, we show that the pore structure parameters in seismic petrophysical theory are highly related to permeability, providing a new solution for predicting permeability using seismic data. Therefore, the correlation between the shear flexibility factor and permeability is first verified based on logging curves and laboratory data, and the results demonstrate that the shear flexibility factor can be an indicator of reservoir permeability. Second, an approximate reflection coefficient equation is derived for the direct characterization of the shear flexibility factor. In the developed equation, a novel fluid indicator, expressed as the ratio of Russell’s fluid indicator to the square of the shear flexibility factor, is defined for the simultaneous prediction of fluid types and permeability. With the validated response of the novel fluid indicator to geofluid types, we achieve simultaneous predictions of fluid types and reservoir permeability characteristics from prestack seismic data, using a boundary-constrained Bayesian inversion strategy. The model tests and the application of field data from a clastic reservoir confirm the effectiveness and applicability of the method.
- Asia > China > Sichuan Province (0.28)
- North America > United States > Texas (0.28)
- Research Report > New Finding (0.34)
- Research Report > Experimental Study (0.34)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.69)
- Geophysics > Seismic Surveying > Seismic Processing > Seismic Migration (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
- Oceania > New Zealand > North Island > Taranaki Basin (0.99)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- (24 more...)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
The pore structures of conventional and unconventional reservoirs have various scales of heterogeneity, which lead to multiple flow mechanisms at different scales. Non-Darcy flow may occur at high and low velocities, at the lower end we have the sub-diffusion that occurs in unconventional resources and that can be captured using a fractional temporal derivative of Darcy's law. In naturally fractured reservoirs, the fractal geometry eliminates the assumptions used in the traditional dual-porosity model, because the geological/geomechanical origins of most fracture networks do not justify them. The fractional and fractal approaches represent two ways to capture anomalous diffusion, which is more overarching than the classical normal diffusion, usually assumed in most numerical simulators. This webinar focuses on the convenience of using the fractional approach to analyze transient pressure and rate field data.
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Pressure transient analysis (1.00)
Relative permeability and capillary pressure are multi-phase flow properties characterized by a SCAL-model that determine the reservoir fluid dynamics for the fields in production and for the new field developments. For Carbon Capture and Storage projects (CCS), multi-phase flow properties are equally important. Interpretation of SCAL experiments and implementation of the SCAL-model for full-field simulations will be shared to highlight the impact of the SCAL model uncertainty on the estimation of the carbon dioxide (CO2) storage resource assessment and plume migration for the Northern Lights project - the world's first open-source CO2 transport and storage infrastructure. Webinar recordings will be available on-demand within 1 business day of the webinar completion. For those who attended the live webinar, your certificate will be available in your "Learner Profile" within 1 business day of the webinar completion
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Core analysis (1.00)
Upon completing this Learning Module assignment, the participant should be able to define the following reservoir properties and understand their importance in the overall reservoir development scheme: rock properties (porosity, permeability, fluid saturation, compressibility, anisotropy), fluid properties (phase behavior, PVT relationships, density, viscosity, compressibility, formation volume factor, gas-oil ratio), rock/fluid interactions (wettability, interfacial tension, capillary pressure, relative permeability), read and understand wellsite descriptions of recovered core material, evaluate the core handling and preservation techniques employed, and select sample intervals for laboratory analysis, generate a procedure for preparing and analyzing selected core samples, specifying the tests to be run and the information to be obtained, describe the laboratory techniques and perform the calculations used for determining rock properties, design procedures for obtaining representative surface and subsurface formation fluid samples, describe procedures for generating PVT analyses of reservoir fluid samples, and interpret the resulting reports, and use published correlations to estimate reservoir fluid properties.
- Reservoir Description and Dynamics > Fluid Characterization > Phase behavior and PVT measurements (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.92)
- Reservoir Description and Dynamics > Reserves Evaluation (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.57)