SS Gas Hydrate: Prediction of Production Test Performances in Eastern Nankai Trough Methane Hydrate Reservoirs Using 3D Reservoir Model

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Abstract The Research Consortium for Methane Hydrate Resources in Japan (MH21 Research Consortium) is planning to conduct production tests targeting methane hydrate (MH) reservoirs located in the Eastern Nankai Trough. Towards the successful implementation of the production tests, MH21 Research Consortium has been evaluating MH reservoirs located in the Eastern Nankai Trough from the viewpoints of geology, geophysics, petrophysics and reservoir/production engineering. Integrating the results of these studies, we have been attempting to construct 3D reservoir models, which have been used to predict the performances of production tests through numerical simulation. This paper presents how we constructed the 3D MH reservoir models integrating the results of the log interpretation and the 3D seismic data analyses. This paper also discusses how the heterogeneities of reservoirs with a different scale such as a fault, dip and change in permeability and a well location affect the test performances referring to the results of the numerical simulation. Eastern Nankai Trough MH reservoirs are composed of alternating beds of sand layers and mud layers in turbidite sediments. First, the frames of the geological models for the vicinity of the candidate test wells including the faults were defined rigorously mainly reflecting the 3D seismic interpretation results. The insides of the frames were then divided into multiple grid layers replicating alternating sand and mud layers. The distribution of the properties of each grid layer such as lithology, porosity, permeability and MH saturation were estimated by geostatistical techniques using well log interpretation results as a hard data and seismic attributes (e.g., amplitude and acoustic velocity) as soft data. Finally, the geological models thus constructed were converted to the reservoir models by incorporating overburden and underburden layers and by specifying initial pressure and temperature. Well production test performances were then predicted through numerical simulation assuming the application of the depressurization method. In addition to the base case run, case studies were conducted to examine the effects of reservoir heterogeneities and of well locations, which revealed that the large scale heterogeneities such as sealing capability and conductivity of faults and formation dip affected the short term production test performances rather than small scale heterogeneities like a small change in permeability. Furthermore, these studies showed the benefit of numerical simulation for the design of a field well test.