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Recent research advances in enhanced CO2 mineralization and geologic CO2 storage
Get PDFEnhanced CO2 mineralization and geologic CO2 storage have received increasing attention as two prominent approaches in combating climate change and fostering sustainable development of human society. This paper aims to explore three emerging areas of research within the realm of enhanced CO2 mineralization and geologic CO2 storage, including enhanced rock weathering, numerical modeling and validation of CO2 storage accounting for the interplay of various trapping mechanisms, and the examination of how reservoir heterogeneity influences the migration of CO2-brine multiphase flow. Discussions highlight the effectiveness of the spectrum induced polarization for monitoring changes in petrophysical and geochemical properties of rocks during enhanced rock weathering. Additionally, the multi-scale heterogeneity of geological formations needs to be carefully characterized, due to the fact that it plays a vital role in CO2 migration. Further research is required to achieve accurate and reliable simulations of convective mixing for field-scale applications.Document Type: PerspectiveCited as: Zhang, C., Wang, Y., Kou, Z., Zhang, L. Recent research advances in enhanced CO2 mineralization and geologic CO2 storage. Advances in Geo-Energy Research, 2023, 10(3): 141-145. https://doi.org/10.46690/ager.2023.12.0
Evaluation of bedding effect on the bursting liability of coal and coal-rock combination under different bedding dip angles
Get PDFRock bursts pose a significant risk to coal mine operation safety. Thus, accurately discriminating coal bursting liabilities is crucial for predicting and preventing rock burst events. To better understand the effects of a varying bedding angle on the crack propagation rule, failure mode and bursting liability level of coal and coal-rock combinations, we propose an optimized machine learning-based model. Additionally, uniaxial compressive tests are conducted using PFC3D software on samples with different bedding angles. The results indicate that, among the nine light gradient boosting machine discriminant models constructed using three data preprocessing methods and three parameter optimization algorithms, the optimal model is identified as the particle swarm optimization-light gradient boosting machine discriminant model based on Z-score standardization method, which exhibits the best stability and has a F1-score of 93.6%. Bedding has a significant impact on the failure modes of two kinds of samples, resulting in an evident bedding effect on their bursting liability. The uniaxial compression strength and bursting energy index of both samples show a reduction-rising trend with an increasing bedding dip angle. However, the bursting liability level of these samples is not affected by 0◦ or 90◦ bedding dip angle. Therefore, when assessing the bursting liability of samples, the influence of coal seam bedding and its dip angles should be thoroughly considered.Document Type: Original articleCited as: Wang, C., Liu, Y., Song, D., Xu, J., Wang, Q., Zhang, S. Evaluation of bedding effect on the bursting liability of coal and coal-rock combination under different bedding dip angles. Advances in Geo-Energy Research, 2024, 11(1): 29-40. https://doi.org/10.46690/ager.2024.01.0
Theoretical assessment of CO2 injection into low-temperature water zones for non-leaking storage in hydrate form
Get PDFConcerns exist about CO2 leaks from conventional supercritical CO2 storage reservoirs. This study investigates injecting CO2 into low-temperature offshore reservoirs to lock it in a solid state, thus preventing potential leaks. An analytical model was developed to predict CO2 injectivity into frac-packed injection wells in these low-temperature reservoirs. While the initial transient flow model was complex with Bessel functions and exponential integral, it was further simplified for practical field application. Sensitivity analysis of the model reveals that injectivity is less sensitive to reservoir permeability but more sensitive to fracture conductivity. The analytical model suggests injectivity is directly proportional to fracture width and fracture permeability. The case study utilizing field data from the South China Sea indicates feasible injection rates ranging from 6 to 17 tons/day depending on fracture conductivity. This work provides an analytical tool to predict injectivity for CO2 storage in frac-packed low-temperature offshore reservoirs, contributing to carbon reduction and neutralization goals.Document Type: Short communicationCited as: Guo, B., Zhang, P. Theoretical assessment of CO2 injection into low-temperature water zones for non-leaking storage in hydrate form. Advances in Geo-Energy Research, 2023, 10(1): 1-6. https://doi.org/10.46690/ager.2023.10.0
Adsorption and desorption characteristics of coal seam gas under infrared radiation
Get PDFInfrared radiation technology can enhance rock permeability and promote methane desorption in coalbed methane thermal recovery. In this study, an experimental system with infrared radiation is developed to investigate the adsorption/desorption behavior of coal under different water contents. The results demonstrate that higher power levels of infrared radiation lead to decreased adsorption capacity and increased desorption capacity in coal. Specifically, employing 50 W infrared radiation results in a 30.9% increase in desorption capacity. Higher moisture content intensifies the desorption hysteresis effect, while this adverse impact can be mitigated by infrared radiation with greater power levels, exhibiting a stronger ability to reduce desorption-induced hysteresis. Additionally, a critical pressure for infrared radiation is established. Before and after this pressure, the influence of infrared radiation power on pressure sensitivity differs significantly. Finally, an improved Langmuir adsorption model considering infrared radiation power and moisture content is proposed and validated using experimental data. Our research expands the application of infrared radiation technology for enhanced coalbed methane recovery during actual mining operations.Document Type: Original articleCited as: Tu, Y., Zhang, Y., Dong, Y., Ma, Y. Adsorption and desorption characteristics of coal seam gas under infrared radiation. Capillarity, 2023, 8(3): 53-64. https://doi.org/10.46690/capi.2023.09.0
Research on the differential tectonic-thermal evolution of Longmaxi shale in the southern Sichuan Basin
Get PDFThe southern Sichuan Basin in China holds abundant shale gas resources; however, the shale gas bearing property shows great differences due to the multiple stages of tectonic transformation. The key to revealing the shale gas differential enrichment mechanism is to explore the thermal evolution characteristics during tectonic evolution. Therefore, taking the Luzhou and Changning blocks as an example, which have obvious differences in tectonic evolution, the organic geochemical conditions of Longmaxi shale were firstly compared with the test data. Then, the thermal evolution characteristics under the background differential tectonic uplift-erosion were recovered using basin modeling techniques. The results showed that the two blocks contain similar organic geochemical conditions of the Longmaxi shale. Moreover, the hydrocarbon generation condition in Luzhou Block is greater than that in the Changning Block. Influenced by the differential tectonic evolution, the study area experienced a complex burial history and the formation of multiple unconformities. As a result, the present burial depth of Longmaxi Formation in the Luzhou Block is significantly greater than that in the Changning Block. The thermal evolution history of Longmaxi shale in the study area could be divided into three stages, including a low-temperature stage from Caledonian to Hercynian, a middle-temperature stage from Hercynian to Indosinian, and a high-temperature stage from Yanshanian to Himalayan. In addition, it was found that the Himalayan period is the main stage resulting in the differential gas bearing property of Longmaxi shale in the southern Sichuan area. Under the differential structural modification, the peak time of hydrocarbon generation in the Luzhou Block occurred earlier and the conversion rate was slightly higher than that in the Changning Block.Document Type: Original articleCited as: Zhao, L., Mao, W., Liu, Z., Cheng, S. Research on the differential tectonic-thermal evolution of Longmaxi shale in the southern Sichuan Basin. Advances in Geo-Energy Research, 2023, 7(3): 152-163. https://doi.org/10.46690/ager.2023.03.0
CO2 storage in depleted oil and gas reservoirs: A review
Get PDFGeological storage of CO2 in depleted oil and gas reservoirs is approved due to its advantages, such as strong storage capacity, good sealing performance, and complete infrastructure. This review clarified the existing projects, advantages, significances, influencing factors, mechanisms, and storage potential evaluation procedures of CO2 storage in depleted oil and gas reservoirs. In this review, the storage capability of depleted oil and gas reservoirs has been confirmed, and factors affecting the CO2 storage potential, including geological factors and engineering factors, are concluded. CO2 trapping mechanisms of different storage processes in depleted oil and gas reservoirs are elaborated and divided into three stages. The evaluation stages of CO2 storage potential of depleted oil and gas reservoirs are summarized as basin selection evaluation stage, oil and gas reservoir selection evaluation stage, storage security evaluation using the bowtie method, and storage capacity calculation stage. The calculation accuracy of CO2 storage capacity in depleted oil and gas reservoirs can be optimized by determining the mineralization storage volume and the actual reservoir characteristics of the dissolution storage coefficient numerically. This work intends to provide support for the storage of CO2 by analyzing and studying the geological theory and engineering achievements of CO2 storage in depleted oil and gas reservoirs.Document Type: Invited reviewCited as: Wei, B., Wang, B., Li, X., Aishan, M., Ju, Y. CO2 storage in depleted oil and gas reservoirs: A review. Advances in Geo-Energy Research, 2023, 9(2): 76-93. https://doi.org/10.46690/ager.2023.08.0
Acoustic impedance inversion in coal strata using the priori constraint-based TCN-BiGRU method
Get PDFAcoustic impedance inversion is a key technique for the seismic exploration of coalfield, which can determine subsurface lithological changes and coal seam distribution. The traditional method is highly subjective, has poor generalizability, and interpretation can be time and labor consuming. Due to the powerful nonlinear interpretation and feature extraction capabilities of neural networks, deep learning technology has demonstrated potential for geophysical exploration. To predict acoustic impedance accurately and efficiently, this study proposes the use of the initial geological model as the priori constraint for training. The low-frequency feature extraction capability of a bidirectional gated recurrent unit network and the high-frequency feature extraction capability of a temporal convolutional network are used to establish a new acoustic impedance inversion method in coal strata with a priori constraint data. The temporal convolutional network-bidirectional gated recurrent unit method was applied to data from the Xinjing Mining Area in Shanxi province, northern China. The results displayed good precision by accurately predicting the distribution and thickness variation of local coal seams. Compared with the traditional model-based method and the method using temporal convolutional network-bidirectional gated recurrent unit network, the proposed priori constraint-based temporal convolutional network-bidirectional gated recurrent unit network has better feature expression capability and provides more detailed coal seam information. In conclusion, the new method can improve the accuracy of acoustic impedance inversion, which is of great significance for coalfield seismic exploration.Document Type: Original articleCited as: Shi, S., Qi, Y., Chang, W., Li, L., Yao, X., Shi, J. Acoustic impedance inversion in coal strata using the priori constraint-based TCN-BiGRU method. Advances in Geo-Energy Research, 2023, 9(1): 13-24. https://doi.org/10.46690/ager.2023.07.0
Pseudopotential-based multiple-relaxation-time lattice Boltzmann model for multicomponent and multiphase slip flow
Get PDFThe microscale liquid flow in nanoscale systems considering slip boundary has been widely studied in recent years, however, they are limited to single-phase flow. As in nature, multicomponent and multiphase flows can also exist with non-zero slip velocities, such as oil/water slip flow in nanoporous shale. In this paper, a novel multicomponent-multiphase multiple-relaxation-time lattice Boltzmann method with a combinational slip boundary condition is developed to study the two-phase slip flow behaviors. The proposed combined slip boundary condition is derived from adjustments to the conventional diffusive Maxwell’s reflection and half-way bounce-back scheme boundary parameters, incorporating a compelled conservation requirement. With the analysis of simulations for the layer, slug, and droplet types of two-phase flow in single pores, and two-phase flow in porous media with complex wall geometry, it can be concluded that the proposed schemes of two-phase slip boundary conditions are particularly suitable for multicomponent and multiphase flow with a non-zero slip velocity. The proposed model can be used to determine relative permeability and simulate spontaneous imbibition in particular in shale reservoirs where those flow properties are hard-to-determine.Document Type: Original articleCited as: Wang, W., Xie, Q., Wang, H., Su, Y., Rezaei-Gomari, S. Pseudopotential-based multiple-relaxation-time lattice Boltzmann model for multicomponent and multiphase slip flow. Advances in Geo-Energy Research, 2023, 9(2): 106-116. https://doi.org/10.46690/ager.2023.08.0
Recent advances in theory and technology of oil and gas geophysics
Get PDFOil and gas are important energy resources and industry materials. They are stored in pores and fractures of subsurface rocks over thousands of meters in depth, making the finding and distinguishing them to be a significant challenge. The geophysical methods, especially the seismic and well-logging methods, are the effective ways to identify the oil and gas reservoirs and are widely used in industry. Due to the complexity of near surface and subsurface structures of new exploration targets, the geophysical methods based on advanced computation methods and physical principles are continuously proposed to cope with the emerging challenges. Thus, some new advances in theory and technology of oil and gas geophysics are summarized in this editorial material, especially focusing on the geophysical data processing, numerical simulation technology, rock physics modeling, and reservoir characterization.Document Type: EditorialCited as: Wang, Y., Liu, Y., Zou, Z., Bao, Q., Zhang, F., Zong, Z. Recent advances in theory and technology of oil and gas geophysics. Advances in Geo-Energy Research, 2023, 9(1): 1-4. https://doi.org/10.46690/ager.2023.07.0
Gas well performance prediction using deep learning jointly driven by decline curve analysis model and production data
Get PDFThe prediction of gas well performance is crucial for estimating the ultimate recovery rate of natural gas reservoirs. However, physics-based numerical simulation methods require a significant effort to build a robust model, while the decline curve analysis method used in this field is based on certain assumptions, hence its applications are limited due to the strict working conditions. In this work, a deep learning model driven jointly by the decline curve analysis model and production data is proposed for the production performance prediction of gas wells. Due to the time-series characteristics of gas well production data, the long short-term memory neural network is selected to establish the architecture of artificial intelligence. The existing decline curve analysis model is first implicitly incorporated into the training process of the neural network and then used to drive the neural network construction along with the actual gas well production historical data. By applying the proposed innovative model to analyze the conventional and tight gas well performance predictions based on field data, it is demonstrated that the proposed long short-term memory neural network deep learning model driven jointly by the decline curve analysis model and production data can effectively improve the interpretability and predictive ability of the traditional long short-term memory neural network model driven by production data alone. Compared with the data-driven model, the jointly driven model can reduce the mean absolute error by 42.90% and 13.65% for a tight gas well and a carbonate gas well, respectively.Document Type: Original articleCited as: Xue, L., Wang, J., Han, J., Yang, M., Mwasmwasa, M. S., Nanguka, F. Gas well performance prediction using deep learning jointly driven by decline curve analysis model and production data. Advances in Geo-Energy Research, 2023, 8(3): 159-169. https://doi.org/10.46690/ager.2023.06.0