摘要
准噶尔盆地西北缘乌尔禾地区云质岩储层较发育,储层物性受裂缝等次生孔隙控制,且单层厚度大,更易形成高效油气藏,是该区油藏评价开发的重要领域之一。但由于云质岩储层横向变化较快、构造落实精度低,导致钻井成功率相对较低,制约了油藏的后续产能建设。本次研究结合GeoEast解释系统中的断层形态指数属性,实现了油藏区的小断裂刻画,落实了控制油藏的4条断裂。纵波阻抗与电阻率曲线交会分析发现,波阻抗曲线可以区分砂泥岩,但无法区分砂岩与云质岩储层,而电阻率曲线却可以区分。因此利用基于电阻率曲线的BP神经网络反演预测了该区云质岩储层的展布特征,结果与实钻井情况吻合较好,对推动该区的油藏评价开发具有积极的现实意义。
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 subsystem,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 res-ervoirs.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.
引文
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