Validation of strongly coupled geomechanics and gas hydrate reservoir simulation with multiscale laboratory tests

Kim, Jihoon; Lee, Joo Yong; Ahn, Tae-Seok; Yoon, Heesung; Lee, Jaehyung; Yoon, Sangcheol; Moridis, George J.

doi:10.1016/j.ijrmms.2021.104958

Cited by 12 publications

(15 citation statements)

References 32 publications

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“…Sequential indicator simulation is a simulation method based on pixel [11] [12] [13]. By calculating the variation function of spatial attribute parameters, a stochastic reservoir model based on the variation function is established.…”

Section: Principle Of Sequential Indication Simulationmentioning

confidence: 99%

Prediction of Sedimentary Microfacies Distribution by Coupling Stochastic Modeling Method in Oil and Gas Energy Resource Exploitation

Wang¹,

Feng²

2023

EPE

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In view of the problem that a single modeling method cannot predict the distribution of microfacies, a new idea of coupling modeling method to comprehensively predict the distribution of sedimentary microfacies was proposed, breaking the tradition that different sedimentary microfacies used the same modeling method in the past. Because different sedimentary microfacies have different distribution characteristics and geometric shapes, it is more accurate to select different simulation methods for prediction. In this paper, the coupling modeling method was to establish the distribution of sedimentary microfacies with simple geometry through the point indicating process simulation, and then predict the microfacies with complex spatial distribution through the sequential indicator simulation method. Taking the DC block of Bohai basin as an example, a high-precision reservoir sedimentary microfacies model was established by the above coupling modeling method, and the model verification results showed that the sedimentary microfacies model had a high consistency with the underground. The coupling microfacies modeling method had higher accuracy and reliability than the traditional modeling method, which provided a new idea for the prediction of sedimentary microfacies.

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Section: Principle Of Sequential Indication Simulationmentioning

confidence: 99%

Prediction of Sedimentary Microfacies Distribution by Coupling Stochastic Modeling Method in Oil and Gas Energy Resource Exploitation

Wang¹,

Feng²

2023

EPE

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“…To date, only short-term production tests have been performed onshore in Alaska , and Canada , and offshore in Japan , and China, , which have produced encouraging results. Reservoir response modeling ,− suggests that gas production from methane hydrates increased during the first several years, which is in contrast to production from other resources, such as shale gas. , With the exclusion of the Arctic/Antarctic methane hydrate accumulations and with oceanic methane hydrates representing 99% of the total global methane hydrate resource, , the U.S. Department of Energy, Gulf of Mexico methane hydrate program is focused on the need for offshore reservoir characterization of coarse-grained methane hydrate reservoirs. , …”

Section: Methane Hydrates As a Massive Bridge Fuel Clean-energy Sourcementioning

confidence: 99%

Energy Transition and Climate Mitigation Require Increased Effort on Methane Hydrate Research

et al. 2022

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“…As aforementioned, the total entropy variation δ Sl is then balanced in terms of the variations of the following: m J , T l , p l,J , and σ. In Equation (21), sl,J is the internal entropy for material l per unit mass of phase J, i.e., the specific entropy of phase J for the material.…”

Section: Mp Materials and Flow And Heat Constitutive Relationsmentioning

confidence: 99%

“…For Equation (21), note also that the volumetric strain term derived from γ l η l K l δσ l v (σ l v is the mean stress of material l) is negligible because the heat source induced by deformation is trivial considering the typical large heat capacity of rock. However, the heat can induce volume change as expressed in Equations ( 1) and (3); thus, the "one-way" coupling is still valid between heat and geomechanics, i.e., from heat to geomechanics only.…”

Section: Mp Materials and Flow And Heat Constitutive Relationsmentioning

confidence: 99%

“…Several simulators exist for coupled flow and geomechanics simulation, especially for the gas hydrates which are either based on the kinetic and equilibrium model, such as MH21 [18], STOMP-HYD-KE [19], or TOUGH+HYDRATE [20]. In this study, we use T+M AM , which is recently developed and validated with multiscale experiments [21]. The T+M AM simulator consists of TOUGH+HYDRATE and ROCMECH [22], which are flow and geomechanics simulators, respectively, for which a mixed formulation-the finite volume (FV) and finite element (FE) methods for fluid and geomechanics, respectively-is taken [23].…”

Section: Introductionmentioning

confidence: 99%

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Integration of Electromagnetic Geophysics Forward Simulation in Coupled Flow and Geomechanics for Monitoring a Gas Hydrate Deposit Located in the Ulleung Basin, East Sea, Korea

Yoon

Kim

et al. 2022

Energies

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We investigate the feasibility of electromagnetic (EM) geophysics methods to detect the dissociation of gas hydrate specifically from a gas hydrate deposit located in the Ulleung Basin, East Sea, Korea via an integrated flow-geomechanics-EM geophysics simulation. To this end, coupled flow and geomechanics simulation is first performed with the multiple porosity model employed, where a mixed formulation with the finite volume (FV) and finite element (FE) methods are taken for the flow and geomechanics, respectively. From the saturation and porosity fields obtained from the coupled flow and geomechanics, the electrical conductivity model is established for the EM simulation. Solving the partial differential equation of electrical diffusion which is linearized using the 3D finite element method (FEM), the EM fields are then computed. For numerical experiments, particularly two approaches in the configuration for the EM methods are compared in this contribution: the surface-to-surface and the surface-to-borehole methods. When the surface-to-surface EM method is employed, the EM is found to be less sensitive, implying low detectability. Especially for the short term of production, the low detectability is attributed to the similarity of electrical resistivity between the dissociated gas (CH4) and hydrate as well as the specific dissociation pattern within the intercalated composites of the field. On the other hand, when the surface-to-borehole EM method is employed, its sensitivity to capture the produced gas flow is improved, confirming its detectability in monitoring gas flow. Hence, the EM geophysics simulation integrated with coupled flow and geomechanics can be a potential tool for monitoring gas hydrate deposits.

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Validation of strongly coupled geomechanics and gas hydrate reservoir simulation with multiscale laboratory tests

Cited by 12 publications

References 32 publications

Prediction of Sedimentary Microfacies Distribution by Coupling Stochastic Modeling Method in Oil and Gas Energy Resource Exploitation

Prediction of Sedimentary Microfacies Distribution by Coupling Stochastic Modeling Method in Oil and Gas Energy Resource Exploitation

Energy Transition and Climate Mitigation Require Increased Effort on Methane Hydrate Research

Integration of Electromagnetic Geophysics Forward Simulation in Coupled Flow and Geomechanics for Monitoring a Gas Hydrate Deposit Located in the Ulleung Basin, East Sea, Korea

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