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Collaborating Authors
Results
An effective multiphysics toolkit for Lithium prospecting: from geophysics to the static reservoir model in Pozuelos salt flat, Argentina.
Curcio, Ana (Proingeo SA) | Chanampa, Eliana (Ltica Resources (a Pluspetrol Mining Co.)) | Cabanillas, Luis (Consultant) | Piethe, Ricardo (Ltica Resources (a Pluspetrol Mining Co.))
The energy transition drives the energy sector to renewable energy and electrification, being the critical minerals key players in the industrial development map. They comprise rare earth elements and 35 other elements including lithium that holds the 60% of its world reserves in the so-called lithium triangle located in Argentina-Bolivia-Chile.The low electrical resistivities, variations in salt concentrations, low acoustic impedances and dynamics of the hydrogeological system, makes brine monitoring a complex geophysical exploratory problem. So, the objective is to find a suitable combination of geophysical techniques that fit the lithium exploration objectives, which are the characterization of the salt flat in depth, fluid detection, basement delineation, definition of the main structures and main faults and detection of semi-fresh water aquifers that contribute to its recharge and that are key to the water balance of the endorheic basin, which has the resource in solution. For this purpose, the evaluation of several prospecting methods in different salt flats was executed, concluding that full tensor magnetotellurics, electrical resistivity tomography and gravity comprises a toolkit that fit the objectives set.#xD;The methodology is validated in Pozuelos salt flat. The results show that the fresh water-brines contact and the recharge system were well defined and understood with the electrical resistivity tomography survey. The full tensor megnetotellurics detects two ultra-conductive units: the shallower one, interpreted as a multilayer system saturated with brines, has 400 m thickness, whereas the deeper one has a 500 thickness. Both magnetotellurics and gravity characterizes the basement and gravity successfully delineated the main structures. The geophysical interpretation is in concordance with shallow and deep exploration wells. Finally, the integration of geophysical and well data allowed the construction of a 3D static reservoir model that finds the deepest basement area at approximately 900 meters depth and discriminates eight lithofacies.
- South America > Argentina (0.71)
- North America > United States (0.67)
- Geology > Mineral (1.00)
- Geology > Rock Type > Sedimentary Rock (0.93)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.36)
- Africa > South Africa > Western Cape Province > Indian Ocean > Bredasdorp Basin > Block 9 > EM Field (0.99)
- South America > Chile (0.95)
- Europe (1.00)
- Asia (1.00)
- North America > United States > Texas (0.67)
- Summary/Review (1.00)
- Instructional Material > Course Syllabus & Notes (1.00)
- Collection > Book (1.00)
- (2 more...)
- Geology > Structural Geology > Tectonics > Plate Tectonics (1.00)
- Geology > Rock Type > Sedimentary Rock (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- (5 more...)
- Asia > Russia > Ural Federal District > Yamalo-Nenets Autonomous Okrug > Purovsky District > West Siberian Basin > Nadym-Pur-Taz Basin > Block V > Urengoyskoye Field > Achimov Formation (0.99)
- Asia > Russia > Ural Federal District > Yamalo-Nenets Autonomous Okrug > Purovsky District > West Siberian Basin > Nadym-Pur-Taz Basin > Block IV > Urengoyskoye Field > Achimov Formation (0.99)
- Asia > Russia > Ural Federal District > Yamalo-Nenets Autonomous Okrug > Purovsky District > West Siberian Basin > Nadym-Pur-Taz Basin > Block 5A > Urengoyskoye Field > Achimov Formation (0.99)
- (4 more...)
On the Evaluation of Coal Strength Alteration Induced by CO2 Injection Using Advanced Black-Box and White-Box Machine Learning Algorithms
Lv, Qichao (National Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum (Beijing) (Corresponding author)) | Zheng, Haimin (Engneering & Design Deptment, CNOOC Research Institute Cooperation) | Li, Xiaochen (CNPC Bohai Drilling Engineering Company Limited) | Mohammadi, Mohammad-Reza (Department of Petroleum Engineering, Shahid Bahonar University of Kerman) | Hadavimoghaddam, Fahimeh (Ufa State Petroleum Technological University) | Zhou, Tongke (Department of Chemical Engineering, University of Manchester) | Mahmoudzadeh, Atena (Department of Petroleum Engineering, Shahid Bahonar University of Kerman) | Hemmati-Sarapardeh, Abdolhossein (Department of Petroleum Engineering, Shahid Bahonar University of Kerman (Corresponding author))
Summary The injection of carbon dioxide (CO2) into coal seams is a prominent technique that can provide carbon sequestration in addition to enhancing coalbed methane extraction. However, CO2 injection into the coal seams can alter the coal strength properties and their long-term integrity. In this work, the strength alteration of coals induced by CO2 exposure was modeled using 147 laboratory-measured unconfined compressive strength (UCS) data points and considering CO2 saturation pressure, CO2 interaction temperature, CO2 interaction time, and coal rank as input variables. Advanced white-box and black-box machine learning algorithms including Gaussian process regression (GPR) with rational quadratic kernel, extreme gradient boosting (XGBoost), categorical boosting (CatBoost), adaptive boosting decision tree (AdaBoost-DT), multivariate adaptive regression splines (MARS), K-nearest neighbor (KNN), gene expression programming (GEP), and group method of data handling (GMDH) were used in the modeling process. The results demonstrated that GPR-Rational Quadratic provided the most accurate estimates of UCS of coals having 3.53%, 3.62%, and 3.55% for the average absolute percent relative error (AAPRE) values of the train, test, and total data sets, respectively. Also, the overall determination coefficient (R) value of 0.9979 was additional proof of the excellent accuracy of this model compared with other models. Moreover, the first mathematical correlations to estimate the change in coal strength induced by CO2 exposure were established in this work by the GMDH and GEP algorithms with acceptable accuracy. Sensitivity analysis revealed that the Spearman correlation coefficient shows the relative importance of the input parameters on the coal strength better than the Pearson correlation coefficient. Among the inputs, coal rank had the greatest influence on the coal strength (strong nonlinear relationship) based on the Spearman correlation coefficient. After that, CO2 interaction time and CO2 saturation pressure have shown relatively strong nonlinear relationships with model output, respectively. The CO2 interaction temperature had the smallest impact on coal strength alteration induced by CO2 exposure based on both Pearson and Spearman correlation coefficients. Finally, the leverage technique revealed that the laboratory database used for modeling CO2-induced strength alteration of coals was highly reliable, and the suggested GPR-Rational Quadratic model and GMDH correlation could be applied for predicting the UCS of coals exposed to CO2 with high statistical accuracy and reliability.
- North America > United States (1.00)
- Asia > China (0.67)
- Europe > United Kingdom > England (0.28)
- Asia > Middle East > Turkey (0.28)
- Overview (1.00)
- Research Report (0.68)
- North America > United States > Texas > Anadarko Basin (0.99)
- North America > United States > Oklahoma > Anadarko Basin (0.99)
- North America > United States > Kentucky > Illinois Basin (0.99)
- (6 more...)
- 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)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
Throughout Earth's history, powerful geological processes have shaped the planet, formed diverse landscapes, and hidden valuable resources. Like silent architects, these processes play a crucial role in creating the world we see today. One important aspect of this geological story is the formation of critical minerals--essential elements for modern technology. These minerals are not random features but are closely tied to the larger narrative of Earth's evolution. Scientists and engineers are exploring the connections between geological processes and the creation of critical mineral deposits to understand better how to identify, extract, and produce these deposits to help meet the demand for resources considered the building blocks of an electrified future.
- Geology > Mineral (1.00)
- Geology > Rock Type > Sedimentary Rock (0.48)
- Materials > Metals & Mining (1.00)
- Government > Regional Government > North America Government > United States Government (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- North America > United States > Wyoming > Powder River Basin (0.99)
- North America > United States > Montana > Powder River Basin (0.99)
Three dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques
Hu, Yanyan (University of Houston) | Wei, Xiaolong (University of Houston, Stanford University) | Wu, Xuqing (University of Houston) | Sun, Jiajia (University of Houston) | Huang, Yueqin (Cyentech Consulting LLC, University of Houston) | Chen, Jiefu (University of Houston)
ABSTRACT Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.
- North America > United States > Texas (0.29)
- North America > Canada > Ontario (0.28)
Detecting and recovering critical mineral resource systems using broadband total-field airborne natural source audio frequency magnetotellurics measurements
Prikhodko, Alexander (Expert Geophysics Limited) | Bagrianski, Andrei (Expert Geophysics Limited) | Wilson, Robert (Expert Geophysics Limited) | Belyakov, Sergey (Qazaq Geophysics) | Esimkhanova, Nurganym (Qazaq Geophysics)
ABSTRACT Airborne geophysical methods offer a substantial advantage compared to ground-based techniques in exploring territories of different sizes, ranging from entire metallogenic provinces to the deposit scale, including those hosting critical minerals. An airborne method with measurements of natural magnetic field variations, known as audio frequency magnetotellurics (a passive field method), significantly increases the depth of investigation and expands the resistivity detection range compared with some controlled-source primary-field methods. We describe the technical solutions used in an airborne electromagnetic passive system with a mobile sensor of the total magnetic field variations and the stationary sensor of electric field variations, and its applications to recovering the complex geology of hydrothermal-magmatic systems often associated with critical minerals. The systemโs ability to explore depths, typically beginning from the near-surface and down to 1โ2ย km, by recording responses in three orthogonal inductive coils over a broad bandwidth from 22ย Hz to 21,000ย Hz allows for mapping resistivities across a broad range. This capability is crucial for obtaining more comprehensive exploration models. Field case studies of the natural field system include application in exploring for unconformity uranium mineralization, along with other associated minerals, epithermal gold and polymetallic-bearing structures, and ferromanganese and polymetallic deposits formed in a continental rift valley. An extra case study involving kimberlites was incorporated as a proven example of the natural field systemโs capability in conducting near-surface and deep investigations. The case histories illustrate the airborne natural electromagnetic field technology capabilities in recovering geoelectric models and their specific patterns.
- North America > Canada (0.97)
- North America > United States (0.93)
- Geology > Rock Type > Igneous Rock (0.69)
- Geology > Structural Geology > Tectonics > Extensional Tectonics (0.54)
- Geology > Mineral > Silicate (0.51)
- (2 more...)
- North America > Canada > Saskatchewan > Myrtle Basin > McArthur Basin > EP 171 > McArthur River Mine (0.99)
- North America > Canada > Saskatchewan > Athabasca Basin (0.99)
- North America > Canada > Alberta > Athabasca Basin (0.99)
- Africa > South Africa > Western Cape Province > Indian Ocean > Bredasdorp Basin > Block 9 > EM Field (0.99)
Integrating earthquake-based passive seismic methods in mineral exploration: Case study from the Gerolekas bauxite mining area, Greece
Polychronopoulou, Katerina (National Technical University of Athens, Seismotech S.A.) | Malinowski, Michal (Polish Academy of Sciences, Geological Survey of Finland) | Cyz, Marta (Geological Survey of Finland) | Martakis, Nikos (Seismotech S.A) | Apostolopoulos, George (National Technical University of Athens) | Draganov, Deyan (Delft University of Technology)
ABSTRACT As the global need for aluminum constantly rises, bauxite is considered to be a critical mineral, and the mining industry is in search of new and effective exploration solutions. In this context, we design and implement a purely earthquake-based passive seismic survey at the Gerolekas bauxite mining site in Greece. It is a very difficult exploration setting, characterized by rough topography, limited accessibility, and a very complex geotectonic regime. We gather a passive seismic data set consisting of four months of continuous recordings (May to August 2018) from 129 stand-alone 3C seismological stations. We then analyze this data set and extract 848 microearthquakes that will serve as sources for the application of local earthquake tomography (LET) and transient-source seismic interferometry (TSI) by autocorrelation. We apply LET to estimate the 3D P- and S-wave velocity models of the subsurface below the study area and TSI by autocorrelation to retrieve the zero-offset virtual reflection responses below each of the recording stations. The velocity models provide a relatively coarse image of a previously completely unexplored part of the mining concession, whereas the higher-resolution virtual reflection imaging illuminates in detail the different interfaces. We also reprocess three lines of legacy active seismic data that were shot in 2003, using the LET P-wave velocity model for depth migration, and confirm the improvement of seismic imaging. Finally, we evaluate the obtained results using well data and jointly interpret them, extracting useful information on the expected target depths and indicating that earthquake-based passive seismic techniques can be an innovative and environmentally friendly option for mineral exploration.
- Europe > Greece (0.71)
- North America > United States (0.46)
- Overview (0.67)
- Research Report (0.46)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (1.00)
- Geology > Mineral (1.00)
- Information Technology > Data Science (0.46)
- Information Technology > Software (0.46)
Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques
Hu, Yanyan (University of Houston) | Wei, Xiaolong (University of Houston, Stanford University) | Wu, Xuqing (University of Houston) | Sun, Jiajia (University of Houston) | Huang, Yueqin (Cyentech Consulting LLC, University of Houston) | Chen, Jiefu (University of Houston)
ABSTRACT Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.
- North America > United States > Texas (0.29)
- North America > Canada > Ontario (0.28)
Detecting and recovering critical mineral resource systems using broadband total-field airborne natural source audio frequency magnetotellurics measurements
Prikhodko, Alexander (Expert Geophysics Limited) | Bagrianski, Andrei (Expert Geophysics Limited) | Wilson, Robert (Expert Geophysics Limited) | Belyakov, Sergey (Qazaq Geophysics) | Esimkhanova, Nurganym (Qazaq Geophysics)
ABSTRACT Airborne geophysical methods offer a substantial advantage compared to ground-based techniques in exploring territories of different sizes, ranging from entire metallogenic provinces to the deposit scale, including those hosting critical minerals. An airborne method with measurements of natural magnetic field variations, known as audio frequency magnetotellurics (a passive field method), significantly increases the depth of investigation and expands the resistivity detection range compared with some controlled-source primary-field methods. We describe the technical solutions used in an airborne electromagnetic passive system with a mobile sensor of the total magnetic field variations and the stationary sensor of electric field variations, and its applications to recovering the complex geology of hydrothermal-magmatic systems often associated with critical minerals. The systemโs ability to explore depths, typically beginning from the near-surface and down to 1โ2ย km, by recording responses in three orthogonal inductive coils over a broad bandwidth from 22ย Hz to 21,000ย Hz allows for mapping resistivities across a broad range. This capability is crucial for obtaining more comprehensive exploration models. Field case studies of the natural field system include application in exploring for unconformity uranium mineralization, along with other associated minerals, epithermal gold and polymetallic-bearing structures, and ferromanganese and polymetallic deposits formed in a continental rift valley. An extra case study involving kimberlites was incorporated as a proven example of the natural field systemโs capability in conducting near-surface and deep investigations. The case histories illustrate the airborne natural electromagnetic field technology capabilities in recovering geoelectric models and their specific patterns.
- North America > Canada (0.97)
- North America > United States (0.93)
- Geology > Rock Type > Igneous Rock (0.69)
- Geology > Structural Geology > Tectonics > Extensional Tectonics (0.54)
- Geology > Mineral > Silicate (0.51)
- (2 more...)
- North America > Canada > Saskatchewan > Myrtle Basin > McArthur Basin > EP 171 > McArthur River Mine (0.99)
- North America > Canada > Saskatchewan > Athabasca Basin (0.99)
- North America > Canada > Alberta > Athabasca Basin (0.99)
- Africa > South Africa > Western Cape Province > Indian Ocean > Bredasdorp Basin > Block 9 > EM Field (0.99)
Integrating earthquake-based passive seismic methods in mineral exploration: Case study from the Gerolekas bauxite mining area, Greece
Polychronopoulou, Katerina (National Technical University of Athens, Seismotech S.A.) | Malinowski, Michal (Polish Academy of Sciences, Geological Survey of Finland) | Cyz, Marta (Geological Survey of Finland) | Martakis, Nikos (Seismotech S.A) | Apostolopoulos, George (National Technical University of Athens) | Draganov, Deyan (Delft University of Technology)
ABSTRACT As the global need for aluminum constantly rises, bauxite is considered to be a critical mineral, and the mining industry is in search of new and effective exploration solutions. In this context, we design and implement a purely earthquake-based passive seismic survey at the Gerolekas bauxite mining site in Greece. It is a very difficult exploration setting, characterized by rough topography, limited accessibility, and a very complex geotectonic regime. We gather a passive seismic data set consisting of four months of continuous recordings (May to August 2018) from 129 stand-alone 3C seismological stations. We then analyze this data set and extract 848 microearthquakes that will serve as sources for the application of local earthquake tomography (LET) and transient-source seismic interferometry (TSI) by autocorrelation. We apply LET to estimate the 3D P- and S-wave velocity models of the subsurface below the study area and TSI by autocorrelation to retrieve the zero-offset virtual reflection responses below each of the recording stations. The velocity models provide a relatively coarse image of a previously completely unexplored part of the mining concession, whereas the higher-resolution virtual reflection imaging illuminates in detail the different interfaces. We also reprocess three lines of legacy active seismic data that were shot in 2003, using the LET P-wave velocity model for depth migration, and confirm the improvement of seismic imaging. Finally, we evaluate the obtained results using well data and jointly interpret them, extracting useful information on the expected target depths and indicating that earthquake-based passive seismic techniques can be an innovative and environmentally friendly option for mineral exploration.
- Europe > Greece (0.71)
- North America > United States (0.46)
- Overview (0.67)
- Research Report (0.46)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (1.00)
- Geology > Mineral (1.00)
- Information Technology > Data Science (0.46)
- Information Technology > Software (0.46)