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Saskatchewan
Numerous surface-felt earthquakes have been spatiotemporally correlated with hydraulic fracturing operations. Because large deformations occur close to hydraulic fractures (HFs), any associated fault reactivation and resulting seismicity must be evaluated within the length scale of the fracture stages and based on precise fault location relative to the simulated rock volumes. To evaluate changes in Coulomb failure stress (CFS) with injection, we conducted fully coupled poroelastic finite-element simulations using a pore-pressure cohesive zone model for the fracture and fault core in combination with a fault-fracture intersection model. The simulations quantify the dependence of CFS and fault reactivation potential on host-rock and fault properties, spacing between fault and HF, and fracturing sequence. We find that fracturing in an anisotropic in-situ stress state does not lead to fault tensile opening but rather dominant shear reactivation through a poroelastic stress disturbance over the fault core ahead of the compressed central stabilized zone. In our simulations, poroelastic stress changes significantly affect fault reactivation in all simulated scenarios of fracturing 50-200 m away from an optimally oriented normal fault. Asymmetric HF growth due to the stress-shadowing effect of adjacent HFs leads to 1.) a larger reactivated fault zone following simultaneous and sequential fracturing of multiple clusters compared to single-cluster fracturing; and 2.) larger unstable area (CFSgt;0.1) over the fault core or higher potential of fault slip following sequential fracturing compared to simultaneous fracturing. The fault reactivation area is further increased for a fault with lower conductivity and with a higher opening-mode fracture toughness of the overlying layer. To reduce the risk of fault reactivation by hydraulic fracturing under reservoir characteristics of the Barnett Shale, the Fort Worth Basin, it is recommended to 1.) conduct simultaneous fracturing instead of sequential; and 2.) to maintain a minimum distance of ~ 200 m for HF operations from known faults.
- North America > Canada (1.00)
- North America > United States > Texas > Travis County > Austin (0.28)
- North America > United States > Texas > Tarrant County > Fort Worth (0.24)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (1.00)
- Geology > Structural Geology > Fault (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- (2 more...)
- South America > Argentina > Patagonia > Neuquén > Neuquen Basin > Vaca Muerta Shale Formation (0.99)
- North America > United States > Wyoming > Green River Basin > Jonah Field (0.99)
- North America > United States > West Virginia > Appalachian Basin (0.99)
- (51 more...)
Seismic Characterization of the Individual Geological Factor with Disentangled Features
Fei, Yifeng (University of Electronic Science and Technology of China (UESTC)) | Cai, Hanpeng (University of Electronic Science and Technology of China (UESTC)) | Zhou, Cheng (University of Electronic Science and Technology of China (UESTC)) | He, Xin (University of Electronic Science and Technology of China (UESTC)) | Liang, Jiandong (University of Electronic Science and Technology of China (UESTC)) | Su, Mingjun (PetroChina) | Hu, Guangmin (University of Electronic Science and Technology of China (UESTC))
Seismic attributes are critical in understanding geological factors, such as sand body configuration, lithology, and porosity. However, existing attributes typically reflect a combined response of multiple geological factors. The interplay between these factors can obscure the features of the target factor, posing a challenge to its direct seismic characterization, particularly when the factor is subtle. To address this, we develop an innovative neural network designed to disentangle and characterize the individual geological factor within seismic data. Our approach divides the geological information in the seismic data into two categories: the single geological factor of interest and an aggregate of all other information. A novel feature-swapping mechanism within our network facilitates the disentanglement of these two categories, providing an interpretable representation. We employ a triplet loss function to differentiate data samples with similar waveforms but varying subtle geological details, thus enhancing the extraction of distinct features. Additionally, our network employs a co-training strategy to integrate synthetic and actual field data during the training process. This strategy helps mitigate potential performance degradation arising from discrepancies between simulated and actual field data. We apply our method to synthetic data experiments and field data from two geologically distinct areas. Current results indicate that our method surpasses traditional approaches such as a deep autoencoder and a convolutional neural network classifier in extracting seismic attributes with more explicit geophysical implications.
- Geology > Rock Type > Sedimentary Rock (0.46)
- Geology > Geological Subdiscipline > Geomechanics (0.45)
More than 1,000 mound structures have been mapped in shallow marine sediments at the Cretaceous Paleogene boundary in the Rub Al-Khali of Saudi Arabia. Mapping utilized 3D reflection seismic data in a 37,000 square kilometer study area. No wells penetrate the mounds themselves. The mounds are at a present-day subsurface depth of approximately 1 km and are convex-up with diameters of 200 400 m and elevation of 10 15 m. The mounds display spatial self-organization with a mean separation of approximately 3.75 km. Comparison with mound populations in other study areas with known spatial distribution statistics and modes of origin indicates that the mound population in this study has the characteristics of fluid escape structures, and they are interpreted here as mud volcanoes. The observation that the mounds occur at the Cretaceous Paleogene boundary demands a singular trigger at that moment in time. We develop a model of seismic energy related mud volcanism mechanism including the Chicxulub asteroid impact as the energy source that accounts for the timing of the mound structures, and a drainage cell model based on producing water wells that provides a mechanism for spatial self-organization into a regular pattern.
- Europe (1.00)
- Asia > Middle East > Saudi Arabia (1.00)
- Africa (1.00)
- Phanerozoic > Cenozoic > Paleogene > Paleocene (0.67)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.46)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment (1.00)
- Geology > Rock Type > Sedimentary Rock (1.00)
- Geology > Geological Subdiscipline > Volcanology (1.00)
- (2 more...)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation > Well Tie (0.46)
- Oceania > New Zealand > South Island > South Pacific Ocean > Great South Basin (0.99)
- North America > Canada > Saskatchewan > Prairie Evaporite Basin (0.99)
- Europe > Norway > North Sea > Central North Sea > Norwegian-Danish Basin (0.99)
- (6 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
The presentation reviews the results of taking three 40/70 mesh proppants commonly used for multi-stage horizontal well slickwater completions in North America and testing them at 0.5 lb/ft2 over 1000 hours of "extended time" at stress and temperature conditions representative of the Bakken formation of North Dakota. The results presented give a clear insight into the degree of damage occurring in the reservoir due to time at stress and temperature.
- North America > Canada > Saskatchewan > Williston Basin > Bakken Shale Formation (0.99)
- North America > Canada > Manitoba > Williston Basin > Bakken Shale Formation (0.99)
The recent significant influx of large amounts of government incentives for a variety of green initiatives including CCS and CCUS has created a rush to drill and complete CO2 injection wells. However, the necessary corrosion data to make informed choices for corrosion resistance in these wells is minimal at best. Some oil and gas professionals have argued that there is no difference between the more than 40 years of petroleum experience with CO2 EOR and planned CCS wells. This comparison is not a valid one and can be risky considering the need for very long-term containment of CO2 required by regulators. This article presents a comparison between CO2 EOR and CCS for injection well metallurgy and explains why this comparison is invalid.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.33)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Mission Canyon Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Madison Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Forbisher Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Charles Formation:Middale Formation (0.99)
- Well Completion > Well Integrity > Subsurface corrosion (tubing, casing, completion equipment, conductor) (1.00)
- Reservoir Description and Dynamics > Storage Reservoir Engineering > CO2 capture and sequestration (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- (3 more...)
Using seismic petrophysical modeling and prestack simultaneous inversion to provide insights into the physical properties of uranium-bearing reservoirs: Implications for favorable sites of sandstone-hosted uranium deposits
Wu, Qubo (China University of Geosciences (Beijing), Beijing Research Institute of Uranium Geology) | Wang, Yanchun (China University of Geosciences (Beijing)) | Huang, Yucheng (Beijing Research Institute of Uranium Geology) | Qiao, Baoping (Beijing Research Institute of Uranium Geology) | Cao, Chengyin (Beijing Research Institute of Uranium Geology) | Li, Ziwei (Beijing Research Institute of Uranium Geology) | Yu, Xiang (China National Uranium Corporation)
ABSTRACT Seismic prospecting has been accepted as one of the most widely available methods for exploring sandstone-hosted uranium deposits (SUDs). However, conventional seismic interpretation faces a challenge in the identification and characterization of a uranium reservoir’s complexity. How to characterize in detail a uranium reservoir’s physical complexity and effectively improve uranium reservoir prediction accuracy remain unresolved problems. To address this, we develop a novel combination of petrophysical modeling and prestack simultaneous inversion to understand in detail the physical properties of uranium-bearing reservoirs and efficiently predict favorable SUD sites. First, we develop a workflow of rock-physics modeling for SUD logs using the Xu-White method to calculate the modulus of elasticity of the grain matrix; subsequently, we extend the Walton model for the modulus prediction of the dry rocks and the Gassmann equation for one of the saturated rocks after a massive calculation test; and then, we predict the S-wave data used for the following inversion. Second, we execute a prestack simultaneous inversion to obtain the petrophysical parameters (e.g., P-impedance, density [], shear modulus [], Lamé coefficient [], and Young’s modulus) that can provide insights into the physical properties of a uranium metallogenic environment. Accordingly, we discover that sites bearing uranium mineralization strongly correspond to areas with low elastic-parameter values (especially and ), whereas nonuranium anomalies occur in high-value sites. This indicates that weakened elastic characteristics are caused by the enhancement of the total organic content and total clay mineral volumes of the uranium-bearing layers. In summary, the developed combination approach can yield an effective and accurate characterization of the geologic properties of uranium-bearing formations, and it can provide prediction factors (e.g., parameters related to the shear modulus) for uranium mineralization.
- Asia > China (1.00)
- North America > Canada (0.68)
- Geology > Mineral > Silicate (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.47)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.37)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Asia > Pakistan > Upper Indus Basin > Potwar Basin (0.99)
- Asia > China > Xinjiang Uyghur Autonomous Region > Junggar Basin (0.99)
- Asia > China > South China Sea > Zhujiangkou Basin (0.99)
- (7 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Health, Safety, Environment & Sustainability > Environment > Naturally occurring radioactive materials (1.00)
ABSTRACT Although trial-and-error modeling may give some level of interpretation about the subsurface while sacrificing certainty, it is a viable alternative for precise 3D interpretation of real ground-airborne frequency-domain electromagnetic (GAFEM) data. In this sense, a semiautomatic trial-and-error modeling approach is developed. Specifically, we first develop the 3D GAFEM forward-modeling code. Its accuracy is demonstrated using a 3D synthetic model with topography and a tilted anomalous body. Second, an initial model is established based on known geologic constraints. Then, the code is conducted repeatedly, and the parameters of the model are renewed semiautomatically based on a predefined geometry-resistivity combination list. Finally, the model that can achieve the minimum error between the computed response and the collected GAFEM data is selected as the final model. Furthermore, we apply the presented semiautomatic trial-and-error modeling approach to the geothermal resources survey at the Yishu Faulting Basin, China. The purpose of the survey is to interpret the resistivity structure of the subsurface and evaluate the potential development of the geothermal resources in the survey area. As a result, the final model obtained by the trial-and-error modeling, which is constrained by the known geologic information and subsurface geoelectric structures inferred from 2D models inverted by the magnetotelluric and controlled-source audio-frequency magnetotelluric data measured at the same location, indicates the existence of the geothermal resources. This indication is proven by the drilling result of a well site located on the survey line. To further verify the reliability, a comparative analysis is conducted between the model obtained by the trial-and-error modeling and the models obtained by 3D inversion of a GAFEM data set and apparent resistivity calculation using the same data. The results indicate that different approaches can achieve similar subsurface geometry and resistivity distribution of the faulting basin structure.
- Asia > China (0.85)
- North America > Canada > Newfoundland and Labrador > Newfoundland (0.28)
- Energy > Oil & Gas > Upstream (1.00)
- Energy > Renewable > Geothermal > Geothermal Resource (0.65)
- North America > Canada > Saskatchewan > Athabasca Basin (0.99)
- North America > Canada > Alberta > Athabasca Basin (0.99)
- North America > Canada > Newfoundland and Labrador > Newfoundland > North Atlantic Ocean > Atlantic Margin Basin > Grand Banks Basin > Flemish Pass Basin (0.95)
- Asia > China > Shandong > Yishu Basin (0.95)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Non-Traditional Resources > Geothermal resources (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
Time-lapse attenuation variations using distributed acoustic sensing vertical seismic profile data during CO2 injection at CaMI Field Research Station, Alberta, Canada
Wang, Yichuan (University of Calgary, CNOOC Research Institute Ltd.) | Lawton, Donald C. (University of Calgary, Carbon Management Canada)
ABSTRACT For seismic monitoring of geologic storage, it is useful to measure time-lapse (TL) variations of seismic attenuation. Seismic attenuation directly connects to different petrophysical parameters within the storage complex. We have developed an approach to derive smooth time-variant amplitude spectra from seismic signals by using the sparse strongest signal peaks, and then measuring two different attributes (conventional Q factor and its “geometric” counterpart) characterizing the path effects of seismic attenuation from the smooth spectra. This approach is straightforward and does not require sophisticated algorithms or parameterization schemes. We apply this approach to TL distributed acoustic sensing (DAS) vertical seismic profile (VSP) data from the Field Research Station (FRS) injection project in southern Alberta, Canada. High-quality stacked reflection records are obtained from the baseline and monitor DAS VSP surveys at the FRS and TL attenuation-attribute differences are derived from these reflection records. TL variations of attenuation are observed within the injection zone at the FRS, which are interpreted as being related to the injected . Although there is always a significant trade-off between the accuracy and temporal resolution of the measured attenuation parameters, reliable attenuation measurements around the injection zone are still achieved with an in-use reflection signal of a sufficient length and bandwidth. Attenuation attributes measured from this approach can be an advantageous tool for monitoring the distribution and migration of plumes.
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Mission Canyon Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Madison Formation (0.99)
- North America > Canada > Saskatchewan > Williston Basin > Weyburn Field > Forbisher Formation (0.99)
- (7 more...)
ABSTRACT Although trial-and-error modeling may give some level of interpretation about the subsurface while sacrificing certainty, it is a viable alternative for precise 3D interpretation of real ground-airborne frequency-domain electromagnetic (GAFEM) data. In this sense, a semiautomatic trial-and-error modeling approach is developed. Specifically, we first develop the 3D GAFEM forward-modeling code. Its accuracy is demonstrated using a 3D synthetic model with topography and a tilted anomalous body. Second, an initial model is established based on known geologic constraints. Then, the code is conducted repeatedly, and the parameters of the model are renewed semiautomatically based on a predefined geometry-resistivity combination list. Finally, the model that can achieve the minimum error between the computed response and the collected GAFEM data is selected as the final model. Furthermore, we apply the presented semiautomatic trial-and-error modeling approach to the geothermal resources survey at the Yishu Faulting Basin, China. The purpose of the survey is to interpret the resistivity structure of the subsurface and evaluate the potential development of the geothermal resources in the survey area. As a result, the final model obtained by the trial-and-error modeling, which is constrained by the known geologic information and subsurface geoelectric structures inferred from 2D models inverted by the magnetotelluric and controlled-source audio-frequency magnetotelluric data measured at the same location, indicates the existence of the geothermal resources. This indication is proven by the drilling result of a well site located on the survey line. To further verify the reliability, a comparative analysis is conducted between the model obtained by the trial-and-error modeling and the models obtained by 3D inversion of a GAFEM data set and apparent resistivity calculation using the same data. The results indicate that different approaches can achieve similar subsurface geometry and resistivity distribution of the faulting basin structure.
- Asia > China (0.85)
- North America > Canada > Newfoundland and Labrador > Newfoundland (0.28)
- Energy > Oil & Gas > Upstream (1.00)
- Energy > Renewable > Geothermal > Geothermal Resource (0.65)
- North America > Canada > Saskatchewan > Athabasca Basin (0.99)
- North America > Canada > Alberta > Athabasca Basin (0.99)
- North America > Canada > Newfoundland and Labrador > Newfoundland > North Atlantic Ocean > Atlantic Margin Basin > Grand Banks Basin > Flemish Pass Basin (0.95)
- Asia > China > Shandong > Yishu Basin (0.95)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Non-Traditional Resources > Geothermal resources (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
Using seismic petrophysical modeling and prestack simultaneous inversion to provide insights into the physical properties of uranium-bearing reservoirs: Implications for favorable sites of sandstone-hosted uranium deposits
Wu, Qubo (China University of Geosciences (Beijing), Beijing Research Institute of Uranium Geology) | Wang, Yanchun (China University of Geosciences (Beijing)) | Huang, Yucheng (Beijing Research Institute of Uranium Geology) | Qiao, Baoping (Beijing Research Institute of Uranium Geology) | Cao, Chengyin (Beijing Research Institute of Uranium Geology) | Li, Ziwei (Beijing Research Institute of Uranium Geology) | Yu, Xiang (China National Uranium Corporation)
ABSTRACT Seismic prospecting has been accepted as one of the most widely available methods for exploring sandstone-hosted uranium deposits (SUDs). However, conventional seismic interpretation faces a challenge in the identification and characterization of a uranium reservoir’s complexity. How to characterize in detail a uranium reservoir’s physical complexity and effectively improve uranium reservoir prediction accuracy remain unresolved problems. To address this, we develop a novel combination of petrophysical modeling and prestack simultaneous inversion to understand in detail the physical properties of uranium-bearing reservoirs and efficiently predict favorable SUD sites. First, we develop a workflow of rock-physics modeling for SUD logs using the Xu-White method to calculate the modulus of elasticity of the grain matrix; subsequently, we extend the Walton model for the modulus prediction of the dry rocks and the Gassmann equation for one of the saturated rocks after a massive calculation test; and then, we predict the S-wave data used for the following inversion. Second, we execute a prestack simultaneous inversion to obtain the petrophysical parameters (e.g., P-impedance, density [], shear modulus [], Lamé coefficient [], and Young’s modulus) that can provide insights into the physical properties of a uranium metallogenic environment. Accordingly, we discover that sites bearing uranium mineralization strongly correspond to areas with low elastic-parameter values (especially and ), whereas nonuranium anomalies occur in high-value sites. This indicates that weakened elastic characteristics are caused by the enhancement of the total organic content and total clay mineral volumes of the uranium-bearing layers. In summary, the developed combination approach can yield an effective and accurate characterization of the geologic properties of uranium-bearing formations, and it can provide prediction factors (e.g., parameters related to the shear modulus) for uranium mineralization.
- Asia > China (1.00)
- North America > Canada (0.68)
- Geology > Mineral > Silicate (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.47)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.37)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Asia > Pakistan > Upper Indus Basin > Potwar Basin (0.99)
- Asia > China > Xinjiang Uyghur Autonomous Region > Junggar Basin (0.99)
- Asia > China > South China Sea > Zhujiangkou Basin (0.99)
- (7 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Health, Safety, Environment & Sustainability > Environment > Naturally occurring radioactive materials (1.00)