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hydrate
- Instructional Material > Course Syllabus & Notes (0.87)
- Instructional Material > Online (0.53)
Rock-physics model of a gas hydrate reservoir with mixed occurrence states
Wu, Cun-Zhi (China University of Petroleum (Beijing)) | Zhang, Feng (China University of Petroleum (Beijing)) | Ding, Pin-Bo (China University of Petroleum (Beijing)) | Sun, Peng-Yuan (CNPC, National Engineering Research Center for Oil and Gas Exploration Computer Software) | Cai, Zhi-Guang (CNPC, National Engineering Research Center for Oil and Gas Exploration Computer Software) | Di, Bang-Rang (China University of Petroleum (Beijing))
ABSTRACT Seismic interpretation of gas hydrates requires the assistance of rock physics. Changes in gas hydrate saturation can alter the elastic properties of formations, and this relationship can be considerably influenced by the occurrence state of gas hydrates. Pore-filling, load-bearing, and cementing types are three single gas hydrate occurrence states commonly considered in rock-physics investigations. However, many gas hydrate-bearing formations are observed to have mixed occurrence states, and their rock-physics properties do not fully conform to models of single occurrence states. We develop a generalized rock-physics model for gas hydrate-bearing formations with three mixed occurrence states observed in the field or laboratory experiments: coexisting pore-filling-type and matrix-forming-type gas hydrates (case 1); pore-filling type when (gas hydrate saturation) < (critical saturation) and pore-filling + matrix-forming type when (case 2); and matrix-forming type when and matrix-forming + pore-filling type when (case 3). Instead of initial porosity, the apparent porosity (the volume fraction of an effective pore filler) represents the influence of occurrence states on the pore space. These three mixed occurrence states can be modeled using a unified workflow, in which the volume fractions of various gas hydrate types are expressed in general forms in terms of the apparent porosity. In addition, the model considers the effect of a pore filler on shear modulus. The developed model is validated through calibration with real well-log data and published experimental data corresponding to five gas hydrate-bearing formations. The model effectively interprets the influences of gas hydrate saturation and occurrence state on these formations. Thus, the generalized model provides a theoretical basis for the analysis of sensitive elastic parameters and quantitative interpretation for gas hydrate reservoirs.
- North America > United States (0.46)
- Asia > China (0.29)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
- Europe > Norway > Norwegian Sea (0.24)
Climate change is known to be dominantly caused by the increased concentration of greenhouse gases in the atmosphere, particularly carbon dioxide (CO2). Over the years, the clathrate hydrate process has demonstrated promising potential for innovative applications, such as natural gas storage, carbon dioxide capture and storage, seawater desalination, and cold energy storage. CO2 hydrate, a solid compound consisting of molecular CO2 encased in crystalline lattices formed by water molecules, is an attractive option for long-term CO2 sequestration. Methane (CH4) hydrates in oceanic sediments have remained stable for millions of years, serving as a natural analog. Thus, the question arises: can we store CO2 in the form of hydrates in oceanic sediments indefinitely?
Machine-learning application to assess occurrence and saturations of methane hydrate in marine deposits offshore India
Chong, Leebyn (National Energy Technology Laboratory, NETL Support Contractor) | Collett, Timothy S. (U.S. Geological Survey) | Creason, C. Gabriel (National Energy Technology Laboratory) | Seol, Yongkoo (National Energy Technology Laboratory) | Myshakin, Evgeniy M. (National Energy Technology Laboratory, NETL Support Contractor)
Abstract Artificial neural networks (ANN) were used to assess methane hydrate occurrence and saturation in marine sediments offshore India. The ANN analysis classifies the gas hydrate occurrence into three types: methane hydrate in pore space, methane hydrate in fractures, or no methane hydrate. Further, predicted saturation characterizes the volume of gas hydrate with respect to the available void volume. Log data collected at six wells, which were drilled during the India National Gas Hydrate Program Expedition 02 (NGHP-02), provided a combination of well-log measurements that were used as input for machine-learning (ML) models. Well-log measurements included density, porosity, electrical resistivity, natural gamma radiation, and acoustic wave velocity. Combinations of well logs used in the ML models provide good overall balanced accuracy (0.79 to 0.86) for the prediction of the gas hydrate occurrence and good accuracy (0.68 to 0.92) for methane hydrate saturation prediction in the marine accumulations against reference data. The accuracy scores indicate that the ML models can successfully predict reservoir characteristics for marine methane hydrate deposits. The results indicate that the ML models can either augment physics-driven methods for assessing the occurrence and saturation of methane hydrate deposits or serve as an independent predictive tool for those characteristics.
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment (1.00)
- Geology > Geological Subdiscipline (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.46)
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.68)
- Asia > India > Andhra Pradesh > Bay of Bengal > Krishna-Godavari Basin (0.99)
- North America > United States > Alaska (0.89)
- North America > Canada (0.89)
This page considers two equilibrium conditions: * The point at which, at a given temperature and pressure, water becomes saturated in either hydrocarbon vapors or hydrocarbon liquids and forms a separate fluid phase. Both water and hydrocarbon dewpoints are represented as the maximum solubility of each phase in the other. Prediction of hydrate formation is covered in Predicting hydrate formation. BecauseF 2, two intensive variables are needed to specify the system. At a given temperature and pressure, the user can determine the saturated water content of gases, the point at which a liquid water phase will precipitate.
- Information Technology > Knowledge Management (0.41)
- Information Technology > Communications > Collaboration (0.41)
Experimental Study on Permeability and Gas Production Characteristics of Montmorillonite Hydrate Sediments Considering the Effective Stress and Gas Slippage Effect
Wu, Zhaoran (School of Vehicle and Energy, Yanshan University) | Gu, Qingkai (School of Vehicle and Energy, Yanshan University) | Wang, Lei (School of Vehicle and Energy, Yanshan University) | Li, Guijing (School of Vehicle and Energy, Yanshan University) | Shi, Cheng (School of Vehicle and Energy, Yanshan University) | He, Yufa (State Key Laboratory of Natural Gas Hydrate) | Li, Qingping (State Key Laboratory of Natural Gas Hydrate) | Li, Yanghui (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology (Corresponding author))
Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology Summary Gas permeability in hydrate reservoirs is the decisive parameter in determining the gas production efficiency and gas production of hydrate. In the South China Sea (SCS), the gas flow in tight natural gas hydrate (NGH) silty clay reservoirs is significantly affected by the gas slippage effect and the effective stress (ES) of overlying rock. To improve the effectiveness of hydrate exploitation, it is necessary to understand the influence of gas slippage in hydrate reservoirs on the permeability evolution law. For this paper, the gas permeability characteristics and methane production of hydrate montmorillonite sediments were studied at different pore pressures and ESs. Experimental data revealed that the gas permeability of montmorillonite samples before methane hydrate (MH) formation is seriously affected by the Klinkenberg effect. The gas permeability of montmorillonite sediments before hydrate formation is generally smaller than that after hydrate formation, and the gas slippage effect in the sediments after hydrate formation is weaker than that before hydrate formation. With the change in ES, the intrinsic permeability of sediment has a power law relationship with the simple ES. As pore pressure decreases and MH decomposes, montmorillonite swelling seriously affects gas permeability. However, the gas slippage effect has a good compensation effect on the permeability of montmorillonite sediments after MH decomposition under low pore pressure. The multistage depressurization-producing process of MH in montmorillonite sediments is mainly 3 MPa depressurization-producing stage and 2 MPa depressurization-producing stage. In this paper, the influence mechanism of gas slippage effect of hydrate reservoir is studied, which is conducive to improving the prediction accuracy of gas content in the process of hydrate exploitation and exploring the best pressure reduction method to increase the gas production of hydrate in the process of exploitation. Introduction As one of the most prospective clean energy sources in the 21st century, NGH mainly exists in permafrost and continental margins of the world's oceans (Sloan Jr. and Koh 2007). MH is the most important component of NGH. MHs are ice-like crystalline compounds in which the host methane molecule is surrounded by a cage of water molecules (Sloan 1998; Li et al. 2023).
- North America > United States (1.00)
- Europe > Norway > Norwegian Sea (0.64)
- Asia > China > Liaoning Province > Dalian (0.24)
- Research Report > New Finding (0.83)
- Research Report > Experimental Study (0.64)
- Asia > China > South China Sea > Yinggehai Basin (0.99)
- Asia > China > South China Sea > Qiongdongnan Basin (0.99)
- South America > Falkland Islands > South Atlantic Ocean > South Falkland Basin > Stokes Prospect > Darwin Formation (0.94)
Steven Constable studied geology at the University of Western Australia, graduating with first class honors in 1979. In 1983 he received a PhD in Geophysics from the Australian National University for a thesis titled "Deep Resistivity Studies of the Australian Crust" and later that year took a postdoc position at the Scripps Institution of Oceanography, University of California - San Diego, where he is currently Professor of Geophysics. Steven is interested in all aspects of electrical conductivity, and has made contributions to inverse theory, electrical properties of rocks, mantle conductivity, magnetic satellite induction studies, global lightning, and instrumentation. However, his main focus is marine electromagnetism; he played a significant role in the commercialization of marine EM for hydrocarbon exploration, work that was recognized by the G.W. Hohmann Award in 2003, the 2007 SEG Distinguished Achievement Award, and now the SEG 2016 [[Reginald Fessenden Award. He also received the R&D 100 Award in 2010, the AGU Bullard Lecture in 2015, followed in 2016 by being named Fellow of the AGU.
- Oceania > Australia > Western Australia (0.35)
- North America > United States > California > San Diego County > San Diego (0.25)
- Geophysics > Electromagnetic Surveying (1.00)
- Geophysics > Seismic Surveying (0.97)
- Information Technology > Knowledge Management (0.40)
- Information Technology > Communications > Collaboration (0.40)
Hydrates are typically methane gas molecules trapped in ice-like crystals of water. The low temperature( 15 C) and high pressure( 5 MPa) conditions of stability for naturally occurring hydrates commonly exists in deep water just beneath the sea floor. The bottom-simulating reflector (BSR) is a reflection event that is closely associated with identifying hydrates in seismic cross-section. Identifying and analyzing hydrates is important. Drilling through hydrates can be challenging, and can cause drilling to be hazardous and cost more.
- Information Technology > Knowledge Management (0.40)
- Information Technology > Communications > Collaboration (0.40)
An Investigation on the Impact of Submicron-Sized Bubbles on the Fragmentation of Methane Clathrates Using Molecular Dynamics Simulation
Tesha, John Michael (State Key Laboratory of Separation Membranes and Membrane Processes, National Center for International Joint Research on Membrane Science and Technology, Tiangong University / School of Materials Science and Engineering, Tiangong University / Tanzania Bureau of Standards (Corresponding author)) | Dlamini, Derrick S. (Department of Civil & Environmental Engineering, University of California / California NanoSystems Institute, University of California) | Mapunda, Edgar Christian (Chemistry Department, University of Dar es salaam) | Kilewela, Ashura Katunzi (Tanzania Bureau of Standards)
Chemistry Department, University of Dar es salaam Summary The formation of submicron-sized bubbles is frequently associated with the fragmentation of methane clathrate. A bubble refers to a pocket or a round particle of one substance trapped inside another. In most cases, these spherical pockets are made of gas trapped inside of a liquid. Usually, bubbles can lie underneath the surface of the liquid until the surface tension breaks and the gas escapes back into the atmosphere. Therefore, understanding the fluid dynamics behavior of the clathrate phase shift and enhancing the production efficiency of natural gas requires knowledge of the impact of submicron-sized bubbles on the clathrate fragmentation. In this scenario, molecular dynamics simulation (MDS) models were carried out to investigate the methane clathrate fragmentation rate with and without preexisting submicron-sized bubbles. The findings demonstrate layer-by- layer fragmentation of the methane clathrate cluster in the liquid phase. Furthermore, this mechanism shows temperature and submicron-sized bubble existence independent of simulation settings or conditions. However, because of the stability of the supersaturated methane solution for a long period, methane clathrate fragmentation does not always result in the formation of submicron-sized bubbles. It was observed that between the bubble (submicron-size) of methane and the cluster surface of methane clathrate, there is a steep slope of methane concentration. Our discoveries in this research show that the existence of submicron-sized bubbles near the surface of the methane clathrate can speed up the rate of intrinsic decomposition while decreasing the activation energy of methane clathrate fragmentation. The mass flow rate is governed by the size of the submicron-sized bubbles and the spacing between the methane clathrate submicron-sized bubbles. Our results contribute to the in-depth knowledge of the fragmentation technique in the liquid phase for methane clathrates, which is critical in optimizing and designing effective gas clathrate development methods. Introduction Natural gas clathrate consists of natural gas compounds, primarily methane, entrapped in water molecules' crystalline matrix at high pressure and low temperature (Dinçer and Zamfirescu 2014).
- Asia (1.00)
- North America > United States > Massachusetts (0.28)
- Africa > Tanzania > Dar es Salaam Region > Dar es Salaam (0.24)
Operators will describe how their best practice hydrate management strategies have evolved. This webinar is categorized under the Projects, Facilities, and Construction discipline. All content contained within this webinar is copyrighted by Speaker Name and its use and/or reproduction outside the portal requires express permission from Speaker Name. Xiaoyun Li is a specialist within hydrate control and Flow Assurance and is currently employed at Equinor ASA in Norway. Prior to working at Equinor, she was a research scientist at Sintef in Trondheim, Norway.
- Instructional Material > Course Syllabus & Notes (1.00)
- Instructional Material > Online (0.95)
- Energy > Oil & Gas > Upstream (1.00)
- Education > Educational Setting > Online (1.00)
- Education > Educational Technology > Educational Software > Computer Based Training (0.89)