Numerical Simulation advances of CCUS in Shale Gas Reservoirs.pptx

Numerical Simulation advances of CCUS in Shale Gas Reservoirs

1. Numerical Simulation Advances in Carbon Capture, Utilization, and Storage (CCUS) in Shale Gas Reservoirs Niranjan Bhore , PhD ( II nd Yr.) Dr. Vishwanath Karad’s MIT World Peace University Presented at ICPHD 2023 IIT Guwahati 3 rd to 5 th Nov 2023

2. Outline ICPHD 2023, IIT Guwahati 2 Niranjan Bhore

3. Introduction ICPHD 2023, IIT Guwahati 3 Niranjan Bhore Fig .1 Fig .2 Fig .3

4. Shale Gas Reservoirs ICPHD 2023, IIT Guwahati 4 Niranjan Bhore Fig .4 Fig .6 Fig .5 Fig .7

5. Numerical Simulation in Reservoir Engineering (Shale Gas Reservoirs) ICPHD 2023, IIT Guwahati 5 Niranjan Bhore Fig .8 Fig .9 Low Permeability: Shale's low permeability hinders CO2 injection and migration. Limits CO2 storage capacity (Cui et al., 2019). Highly Heterogeneous: Variations in composition, porosity, and content affect CO2 behavior predictions ( Javadpour et al., 2017). Geochemical Reactions: CO2 can react with shale, altering its properties. Potential release of contaminants ( Javadpour et al., 2017; Carroll et al., 2014). Risk of Leakage: Natural fractures, faults, and abandoned wells can provide leakage pathways (Celia et al., 2015). Regulatory & Monitoring Challenges: Complexity necessitates stringent monitoring and regulation ( Bachu et al., 2015).

6. Challenges in Shale Gas Reservoirs for CCUS ICPHD 2023, IIT Guwahati 6 Niranjan Bhore Fig .10 Fig .11

7. Advantages in Shale Gas Reservoirs for CCUS ICPHD 2023, IIT Guwahati 7 Niranjan Bhore Fig .12 Fig .14 Fig .13 Fig .15

8. Recent Advances in Numerical Simulation for CCUS Simulation Techniques Description 1. Generalized Ono-Kondo Lattice (OK) Model Predicted the adsorption amount of CH4/CO2 under supercritical, high-pressure conditions. 2. Discrete Fracture Network (DFN) Model Characterized hydraulic fracture networks using micro-seismic monitoring data and engineering analysis. 3. Multiple Interacting Continua (MINC) & Fractal Theories Modeled porous flow in shale matrix. 4. Multiscale Numerical Model (with unstructured tri-prism grids and CVFE method) Used for comprehensive simulations of the reservoir. 5. Discrete Fracture Network (DFN) model Utilized to provide an efficient estimate of the fracture complexity and the distance between orthogonal fractures. 6. Molecular Dynamics (MD) simulations Study performance of scCO2 in shale inorganic nanopores for enhanced oil recovery (EOR) purposes. Analyze flow properties and intermolecular forces of confined scCO2. 7. Coupled numerical fluid dynamics simulation Used along with the static 3D model to study CO2 injection, improve natural gas recovery, and assess CO2 burial potential. 8. Finite element method solving PDEs Simulate realistic CO2 sequestration processes in depleted shale formations. CO2 adsorption, diffusion, dissolution, Darcy flow, and slip flow in multiple scale systems 9. Deep fully connected neural network (FCNN) Hybrid training method combining physics-informed and data-driven neural networks ICPHD 2023, IIT Guwahati 8 Niranjan Bhore Table 2: Emerging simulation techniques for CCUS in Shale Gas Reservoirs Fig. 16

9. Recent Advances in Numerical Simulation for CCUS Importance of high-fidelity models and computational efficiency Method Application Range Advantages Volumetric-based methodology Reservoirs with homogeneous geological structure and simple fluid distribution Simple and convenient Production history-derived estimation methodology Reservoirs with high quality production data Fast and cost-effective Numerical simulation technique Wide range of applications under the correct description of CO2 transport processes Accurate, wide application range and robust Multi-scale model CO2 transport and storage in shale reservoirs Fast and accurate Feature tNavigator CMG Eclipse 300 MRST Structural trapping with geomechanics ✓ ✓ ✓ ✓ Residual saturation trapping ✓ ✓ ✓ ✓ Dissolution trapping ✓ ✓ ✓ ✓ Mineralization trapping ✓ ✓ ✓ ✓ Grid construction ✓ ✓ ✓ ✓ Seismic well tie ✓ ✓ ✓ ✓ Domain conversion ✓ ✓ ✓ ✓ Structural and property modelling ✓ ✓ ✓ ✓ Fully implicit geomechanics ✓ ✓ ✓ - Integrated asset modelling ✓ ✓ ✓ - Long-term effects modelling ✓ ✓ ✓ ✓ Gas trapping effects due to hysteresis - ✓ - - Water phase density and viscosity alteration - ✓ - - Mineral precipitation and dissolution mechanisms - ✓ - - Aqueous phase chemical equilibrium calculations - ✓ - - Extensive library of aqueous and mineral reactions - ✓ - - Cloud technologies - - ✓ - High-resolution reservoir simulator - - ✓ - Uncertainty analysis ✓ ✓ ✓ ✓ ICPHD 2023, IIT Guwahati 9 Niranjan Bhore Table 4: Industrial simulators and their handling capabilities of CCUS simulations Table 3: Computational advantages of various simulation methods

10. Recent Advances in Numerical Simulation for CCUS Study Reservoir Simulation Techniques Used Approach Used Specific Scenarios Addressed P. A. Eigbe et al. 1. Streamline Simulations 2. Vertical Equilibrium Models 3. Inversion Percolation Methods 4. Conventional 3-D Simulations 5. Finite Difference Explicit and Implicit Methods 1. Numerical Modeling 2. Application of Various Models 3. Specific Scenarios Addressed 4. Research Gaps and Future Directions 1. Crossing thermodynamic phase boundaries in CO2 geological storage 2. Analysis of pressure distribution in a hydrocarbon reservoir Yan-Wei Wang et al. 1. Reservoir Parameter Inversion 2. Multi-Objective Optimization 3. Prediction of Dynamic Changes Deep learning technique for analysis of model parameters and injection performance results Not specified Yanwei Wang et al. 2022 Mathematical analysis of Brownian motion equation Analysis of the effects of temperature on Brownian motion, and Klinkenberg effect on CO2 storage in shale reservoirs Impact of the Klinkenberg effect on CO2 storage in shale reservoirs Rui-hang Zhang et al. 1. Generalized Ono-Kondo Lattice (OK) Model 2. Discrete Fracture Network (DFN) Model 3. Multiple Interacting Continua (MINC) and Fractal Theories 4. Multiscale Numerical Model 5. Hybrid Model combining DFN and MINC Analysis of adsorption behavior of CH4 and CO2 in Longmaxi shale samples, and optimization of CO2 storage and EGR 1. Supercritical CO2 for CO2 storage and EGR 2. CO2's higher adsorption ability compared to CH4 3. Longmaxi shale as a potential site for CO2 sequestration Honggang Sui et al. Molecular dynamics simulations Investigation into mechanisms governing CO2-enhanced shale oil recovery within kerogen pores 1. Oil storage behavior, density curves, adsorption layers, flooding behavior, and displacement mechanisms of CO2 in kerogen pores 2. CO2 storage capacity in kerogen pores R Xu et al. TP-DK Model & Fracture Network (DFN model and Orthogonal Unstructured Fracture Model) Comprehensive analysis of fluid dynamics in hydraulic fractures in shale reservoirs Not specified A Hamza et al. Molecular dynamics (MD) simulations, Lattice – Boltzmann (LB) plus MD Understanding of scCO2 behavior in reservoir conditions and prediction of natural gas displacement processes 1. Reservoir heterogeneity, geochemical, and geomechanical parameters in CO2 reactivity and injectivity 2. Reservoir thickness, permeability, and heterogeneity influencing CO2 flow and injectivity ICPHD 2023, IIT Guwahati 10 Niranjan Bhore Table 5: Literature Survey on innovative simulation techniques used in CCUS context

11. Recent Advances in Numerical Simulation for CCUS ICPHD 2023, IIT Guwahati 11 Niranjan Bhore Fig.18 Fig.17 Fig.19 Fig.20

12. Benefits of these Advances Enhanced accuracy in predictions. ICPHD 2023, IIT Guwahati 12 Niranjan Bhore Fig. 21 Fig. 23 Fig. 24 Fig. 22

13. Benefits of these Advances Potential increase in carbon storage capacity in shale reservoirs. ICPHD 2023, IIT Guwahati 13 Niranjan Bhore Fig. 26 Fig. 25 Fig. 28 Fig. 27

14. Future Outlook and Research Directions ICPHD 2023, IIT Guwahati 14 Niranjan Bhore

15. Conclusion ICPHD 2023, IIT Guwahati 15 Niranjan Bhore

16. References A.K. Dahaghi , Numerical Simulation and Modeling of Enhanced Gas Recovery and CO2 Sequestration in Shale Gas Reservoirs: A Feasibility Study, 2010. Paper presented at the SPE International Conference on CO2 Capture, Storage, and Utilization, New Orleans, Louisiana, USA. D. Liu, R. Agarwal, Y. Li, Numerical simulation and optimization of CO2 enhanced shale gas recovery using a genetic algorithm, J. Clean. Prod. 164 (2017) 1093e1104. D. Liu, Y. Li, S. Yang, Evaluation of the role of water-shale-gas reactions on CO2 enhanced shale gas recovery, Energy Proc. 154 (2018) 42e47. F. Liu, K. Ellett , Y. Xiao, J.A. Rupp, Assessing the feasibility of CO2 storage in the New Albany Shale ( DevonianeMississippian ) with potential enhanced gas recovery using reservoir simulation, Int. J. Greenh . Gas Control 17 (2013). H. Sun, J. Yao, S.-h. Gao, D.-y. Fan, C.-c. Wang, Z.-x. Sun, Numerical study of CO2 enhanced natural gas recovery and sequestration in shale gas reservoirs, Int. J. Greenh . Gas Control 19 (2013) 406e419. J. Liu, L. Xie, Y. Yao, Q. Gan, P. Zhao, L. Du, Preliminary study of influence factors and estimation model of the enhanced gas recovery stimulated by carbon dioxide utilization in shale, ACS Sustain. Chem. Eng. 7 (24) (2019) 20114e20125. K.C. Schepers , B.C. Nuttall, A.Y. Oudinot , R.J. Gonzalez, Reservoir Modeling and Simulation of the Devonian Gas Shale of Eastern Kentucky for Enhanced Gas Recovery and CO2 Storage, 2009. Paper presented at the SPE International Conference on CO2 Capture, Storage, and Utilization, San Diego, California, USA. M. Godec, G. Koperna , R. Petrusak , A. Oudinot , Potential for enhanced gas recovery and CO2 storage in the Marcellus Shale in the Eastern United States, Int. J. Coal Geol. 118 (2013) 95e104. R. Xu, K. Zeng, C. Zhang, P. Jiang, Assessing the feasibility and CO2 storage capacity of CO2 enhanced shale gas recovery using Triple-Porosity reservoir model, Appl. Therm. Eng. 115 (2017) 1306e1314. S. Mahdi, X. Wang, N. Shah, Interactions between the design and operation of shale gas networks, including CO2 sequestration, Engineering 3 (2) (2017) 244e256. T.H. Kim, S.S. Park, K.S. Lee, Modeling of CO2 Injection Considering Multi-Component Transport and Geomechanical Effect in Shale Gas Reservoirs, 2015 (Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, Nusa Dua, Bali, Indonesia). W. Yu, E.W. Al- Shalabi , K. Sepehrnoori , A Sensitivity Study of Potential CO2 Injection for Enhanced Gas Recovery in Barnett Shale Reservoirs, 2014. Paper presented at the SPE Unconventional Resources Conference, The Woodlands, Texas, USA. X. Li, D. Elsworth , Effect of CO2 Injectivity on Enhanced Shale Gas Recovery, 2014. Paper presented at the 48th U.S. Rock Mechanics/Geomechanics Symposium, Minneapolis, Minnesota. ICPHD 2023, IIT Guwahati 16 Niranjan Bhore

17. Appendix – Figures, Charts & Tables ICPHD 2023, IIT Guwahati 17 Niranjan Bhore No Description Reference Fig. 1 Schematic diagram of possible CCS systems IPCC 2005 Fig. 2 CO2 Post combustion capture plant in Malaysia IPCC 2005 Fig. 3 Global CO2 emissions from fossil fuel combustions and other industries IPCC 2005 Fig. 4 The geometry of conventional and unconventional natural gas resources. EIA Fig. 5 Hydraulic fracturing as a multiscale and multi-physics process Bin Chen et al., 2022 Fig. 6 Proven reservers of Shale Gas Globally EIA Fig. 7 Avenues of CO2 sequestration within O&G reservoirs EIA Fig. 8 Reservoir simulation process loop BigLoop, Aspen SSE Fig. 9 Mathematical representation of dynamic reservoir model RMS, Aspen SSE Fig. 10 Multiphase transport process during CO2 storage process YanWei Wang et al., 2022 Fig. 11 Spearman correlation between shale properties and incremental CH4 Moataz Mansi et al., 2023 Fig. 12 Diagram of carbon capture and sequestration. Patrick A Eigbe et al., 2023 Fig. 13 Three stages of CO2 adsorption in competition with CH4 W Wang et al., 2023 Fig. 14 Storage expressed as a combination of physical and geochemical trapping. The level of security is proportional to distance from origin IPCC 2005 Fig. 15 Storage security depends on a combination of physical and geochemical trapping IPCC 2005 Fig. 16 Simulation advances over the years for CCUS in Shale Gas reservoirs Modified after Patrick A Eigbe et al., 2023 Fig. 17 DFN Model and discretization of Longmaxi shale R-h Zhang et al., 2021 Fig. 18 Multiscale transport processes during CO2 storage in shale reservoirs YanWei Wang et al., 2022 Fig. 19 Physical model of CO2 transport mechanisms in the shale formation with closed boundary at different scales YanWei Wang et al., 2022 Fig. 20 Schematic diagram of the hybrid physics-informed data-driven neural network (HPDNN) structure YanWei Wang et al., 2023 Fig. 21 Influence of slippage coefficient on CO2 storage in shale. YanWei Wang et al., 2023 Fig. 22 Influence of mobility ratio on CO2 storage in shale. YanWei Wang et al., 2023 Fig. 23 Influence of solubility coefficient on CO2 storage in shale. YanWei Wang et al., 2023 Fig. 24 Influence of adsorption index on CO2 storage in shale. YanWei Wang et al., 2023 Fig. 25 Cumulative gas production volumes with and without CO2 injection Ruina Xu et al., 2017 Fig. 26 Cumulative CO2 storage volume with different production pressures Ruina Xu et al., 2017 Fig. 27 Cumulative CH4 and CO2 ad/desorption of depletion and huff-npuff cases Rui-Han Zhang et al., 2021 Fig. 28 Cumulative CO2 sequestration volume and enhanced shale gas recovery during the depressurization stage. Ruina Xu et al., 2017 Fig. 29 Location or sites where CO2 storage is underway IPCC 2005 Fig. 30 Large-scale CO2 sequestration projects in operation by year Global status of CCS summary report. 2015

18. Thank you! 18 Niranjan Bhore ICPHD 2023, IIT Guwahati

19. Future Outlook and Research Directions ICPHD 2023, IIT Guwahati 19 Niranjan Bhore Fig. 30 Fig. 29