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Automatic well test interpretation based on convolutional neural network for a radial composite reservoir
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LI Daolun,LIU Xuliang,ZHA Wenshu,YANG Jinghai,LU Detang
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Table 4 Basic parameters of 6 field cases.
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| Field case | Formation thickness/m | Porosity/
% | Total compressibility/10-3 MPa-1 | Fluid viscosity/(mPa·s) | Volume
factor | Well
radius/m | Production time/h | Production or injection rate/(m3·d-1) | Shut-in time/h | | 1 | 29.3 | 25.5 | 1.413 | 0.734 | 1.005 | 0.1 | 4 320 | 37.90 | 72 | | 2 | 53.8 | 25.5 | 1.059 | 0.600 | 1.000 | 0.1 | 2 688 | 90.00 | 72 | | 3 | 5.2 | 26.0 | 1.288 | 1.020 | 1.015 | 0.1 | 4 320 | 68.54 | 72 | | 4 | 22.3 | 25.5 | 1.059 | 0.600 | 1.000 | 0.1 | 6 336 | 120.00 | 72 | | 5 | 3.6 | 25.5 | 1.059 | 0.600 | 1.000 | 0.1 | 4 320 | 20.00 | 72 | | 6 | 26.4 | 26.0 | 1.223 | 0.936 | 1.011 | 0.1 | 4 320 | 127.73 | 72 |
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