• Energy Research

Summary The simulation of the in-situ conversion process (ICP) is a challenging endeavor that involves complicated thermal-reactive-compositional coupling processes. The upscaling of ICP simulation has been investigated, but the developed methods have significant limitations, which hinder their use in complicated models. The most constraining limitation of previous ICP upscaling techniques is that they all require modifications of the simulation code, which make them difficult to use in closed-source commercial simulators. In this paper, we introduce a novel upscaling method for ICP simulation. In this new method, we introduce two correction factors (namely α and β in this paper) to adjust the coarse-scale reaction frequency factor and activation energy. The calculation of the two factors is based on the reactions on both coarse-scale and fine-scale models. The new upscaling method does not entail any additional modifications of the underlying simulation source code, and thus it is more feasible to implement. We demonstrate the accuracy and efficiency of our upscaling method with 2D and 3D models, respectively. Apart from model dimensions, the availability of the novel upscaling method for ICP simulations with different values of kinetic parameters is considered as well. It is shown that the novel upscaling method provides reasonably accurate results, and significant computational savings are also achieved.

Summary The simulation of the in-situ conversion process (ICP) is a challenging endeavor that involves complicated thermal-reactive-compositional coupling processes. The upscaling of ICP simulation has been investigated, but the developed methods have significant limitations, which hinder their use in complicated models. The most constraining limitation of previous ICP upscaling techniques is that they all require modifications of the simulation code, which make them difficult to use in closed-source commercial simulators. In this paper, we introduce a novel upscaling method for ICP simulation. In this new method, we introduce two correction factors (namely α and β in this paper) to adjust the coarse-scale reaction frequency factor and activation energy. The calculation of the two factors is based on the reactions on both coarse-scale and fine-scale models. The new upscaling method does not entail any additional modifications of the underlying simulation source code, and thus it is more feasible to implement. We demonstrate the accuracy and efficiency of our upscaling method with 2D and 3D models, respectively. Apart from model dimensions, the availability of the novel upscaling method for ICP simulations with different values of kinetic parameters is considered as well. It is shown that the novel upscaling method provides reasonably accurate results, and significant computational savings are also achieved.

Natural gas hydrates (NGHs) are regarded as a new energy resource with great potential and wide application prospects due to their tremendous reserves and low CO2 emission. Permeability, which governs the fluid flow and transport through hydrate-bearing sediments (HBSs), directly affects the fluid production from hydrate deposits. Therefore, permeability models play a significant role in the prediction and optimization of gas production from NGH reservoirs via numerical simulators. To quantitatively analyze and predict the long-term gas production performance of hydrate deposits under distinct hydrate phase behavior and saturation, it is essential to well-establish the permeability model, which can accurately capture the characteristics of permeability change during production. Recently, a wide variety of permeability models for single-phase fluid flowing sediment have been established. They typically consider the influences of hydrate saturation, hydrate pore habits, sediment pore structure, and other related factors on the hydraulic properties of hydrate sediments. However, the choice of permeability prediction models leads to substantially different predictions of gas production in numerical modeling. In this work, the most available and widely used permeability models proposed by researchers worldwide were firstly reviewed in detail. We divide them into four categories, namely the classical permeability models, reservoir simulator used models, modified permeability models, and novel permeability models, based on their theoretical basis and derivation method. In addition, the advantages and limitations of each model were discussed with suggestions provided. Finally, the challenges existing in the current research were discussed and the potential future investigation directions were proposed. This review can provide insightful guidance for understanding the modeling of fluid flow in HBSs and can be useful for developing more advanced models for accurately predicting the permeability change during hydrate resources exploitation.

Natural gas hydrates (NGHs) are regarded as a new energy resource with great potential and wide application prospects due to their tremendous reserves and low CO2 emission. Permeability, which governs the fluid flow and transport through hydrate-bearing sediments (HBSs), directly affects the fluid production from hydrate deposits. Therefore, permeability models play a significant role in the prediction and optimization of gas production from NGH reservoirs via numerical simulators. To quantitatively analyze and predict the long-term gas production performance of hydrate deposits under distinct hydrate phase behavior and saturation, it is essential to well-establish the permeability model, which can accurately capture the characteristics of permeability change during production. Recently, a wide variety of permeability models for single-phase fluid flowing sediment have been established. They typically consider the influences of hydrate saturation, hydrate pore habits, sediment pore structure, and other related factors on the hydraulic properties of hydrate sediments. However, the choice of permeability prediction models leads to substantially different predictions of gas production in numerical modeling. In this work, the most available and widely used permeability models proposed by researchers worldwide were firstly reviewed in detail. We divide them into four categories, namely the classical permeability models, reservoir simulator used models, modified permeability models, and novel permeability models, based on their theoretical basis and derivation method. In addition, the advantages and limitations of each model were discussed with suggestions provided. Finally, the challenges existing in the current research were discussed and the potential future investigation directions were proposed. This review can provide insightful guidance for understanding the modeling of fluid flow in HBSs and can be useful for developing more advanced models for accurately predicting the permeability change during hydrate resources exploitation.

AbstractEnhanced Gas Recovery by injecting CO2 is one of the efficient scenarios to accelerate gas production if the excessive mixing can be avoided in the process of CO2-CH4 displacement. A laboratory investigation was presented to describe the detailed CO2-CH4 displacement and analyze CO2 dispersion into CH4 in the sand pack for pressure of 10-14MPa at 40°C with the CO2 injection rate of 0.2, 0.3 and 0.4ml/min. And the displacement process was scanned by an X-ray micro-CT scanner. The results of CT scan images were consistent with the breakthrough profile obtained from outlet gas composition analysis. The dispersion coefficient is in the range from 4.478×10-7 to 9.898×10−7mm2/s and it increase with interstitial velocity of CO2 and decrease with pressure. The dispersivity of BZ04 sand pack is calculated as 0.0054 m.

AbstractEnhanced Gas Recovery by injecting CO2 is one of the efficient scenarios to accelerate gas production if the excessive mixing can be avoided in the process of CO2-CH4 displacement. A laboratory investigation was presented to describe the detailed CO2-CH4 displacement and analyze CO2 dispersion into CH4 in the sand pack for pressure of 10-14MPa at 40°C with the CO2 injection rate of 0.2, 0.3 and 0.4ml/min. And the displacement process was scanned by an X-ray micro-CT scanner. The results of CT scan images were consistent with the breakthrough profile obtained from outlet gas composition analysis. The dispersion coefficient is in the range from 4.478×10-7 to 9.898×10−7mm2/s and it increase with interstitial velocity of CO2 and decrease with pressure. The dispersivity of BZ04 sand pack is calculated as 0.0054 m.

Recent advances in computer and data sciences have made artificial intelligence techniques a useful tool in tackling the problems in petroleum exploration and production [...]

Recent advances in computer and data sciences have made artificial intelligence techniques a useful tool in tackling the problems in petroleum exploration and production [...]

Abstract Natural gas hydrate (NGH) will be one of the major future energy sources due to its properties of clean energy and large reserves. Depressurization is proposed as an effective method to extract natural gas from hydrate, however, the gas production from hydrate dissociation may be interrupted by ice generation and hydrate re-formation due to insufficient heat supply in the single depressurization process. To solve this issue, this work conducted simulation on accelerating gas production from the depressurization-induced methane hydrate by electrical heating. The continuous heating and intermittent heating modes were employed and then the electrical heating scheme was optimized for the comprehensive effect of high energy efficiency and high gas production rate. The results show that electrical heating is conducive to gas production from hydrate dissociation at a rapid rate. In the continuous heating, a high initial hydration saturation, low initial water saturation, low specific heat capacity, and high thermal conductivity result in the high gas generation rate and efficient electrical energy utilization (a large energy efficiency ratio). The intermittent heating has a higher efficient utilization of electrical energy than continuous heating. The optimal scheme is determined as the first-half heating type with the optimized electrical heating power of 25.6 W and the heating time of 12.5 min by the gradient descent method of AdaGrad. Compared to the baseline continuous heating case, the energy efficiency ratio (10.70) of the optimal scheme is enhanced by 24.7% with the average gas production rate (2.55 SmL/s) enhanced by 18.2%. It's hoped that the findings of this work can provide some insights into extracting natural gas from gas hydrate deposits.