Abstract:Dolomitic reservoirs were well developed in the northwestern margin of the Wuerhe area, Junggar Basin. These reservoirs are characterized by secondary fracture porosity and thick layers, so they are usually rich hydrocarbon reservoirs, and also are the major targets of the reservoir evaluation and development. But this kind of dolomitic reservoirs usually show rapid lateral variation of thickness, so the precision of structure prediction is low. As a result, the drilling success rate was relatively low and the successive productivity construction was limited. Using fault morphological index attri-butes provided by GeoEast interpretation sub-system, we carry out minor fault description in the study area, and 4 faults controlling oil reservoirs are depicted. With the resistivity and P-wave impedance crossplot analysis, P-wave impedance can distinguish sand and mudstone reservoirs, but cannot distinguish sand reservoirs from dolomitic reservoirs. The resistivity can distinguish sand and dolomite reservoirs. Finally we predict dolomitic reservoir distribution using BP neural network inversion based on resistivity curves. Our prediction has a good agreement with drilled well data, which shows a great potential for the future reservoir evaluation and development in the area.
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