山东HM凹陷含油气性综合定量评价
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摘要
从构造油气藏评价出发,按构造分区将HM凹陷总体划分为凹陷—向斜面、背斜—鼻状—披覆构造、地层超覆缓坡带、断裂陡坡带、隆起—凸起区等五大类。按1∶20万比例尺1cm×1cm进行网格单元划分,对各构造地质体进行变量取值,结合主要生储层沙三段的分布特征、T_1—T_r地震反射特征、γ能谱测量和重磁场分析,依据综合评价指标与已知油气藏之间的内在联系,建立了含油气性圈闭的定量模式。以地质异常值、沙三段砂岩含量、沙三段砂岩总厚、沙三段泥岩总厚、沙三段泥砂比、T_1T_r地震反射等深度、线积分异常、γ能谱测量异常值、重磁处理有关信息等18个指标作为输入层特征向量,进行了ART和BP人工神经网络含油气性综合评价。含油气性有利度高值区与已知油气田吻合,圈定了进一步油气勘查的有利区17个,据含油气性有利度的大小和所处的地质环境划分出一级有利区9个,二级有利区8个。
Proceeding from the evaluation of structural oil-gas deposits,five structural subareas in the Huiming hollow,Shandong,are distinguished:hollow-synclinal limb,anticline-nose-drape structure, stratal onlap-gentle slope zone,fault-steep slope zone,and uplift-rise area.According to a 1 cm×1 cm grid each structural geologic body is quantified.Then a quantification model of oil-gas traps is constructed according to the distribution characteristics of the Sha-3 Member of source and reservoir rocks,T_1-T_r seismic reflection features γ-ray spectrometry and gravity and magnetic analyses,as well as based on the inner relations between the synthetic evaluation indicalors and the known oil-gas deposits.Adaptive Resonance Theory (ART) and Back-Propagation (BP) artificial neural network (ANN) evaluation of oil-gas potentials are made using eighteen indicators such as geologic anomaly values.The high-value favorable regions coincide with the known oil-gas fields.A total of 17 favorable areas for further oil-gas exploration,including 9 first-class and 8 second-class favorable areas, have been delineated according to the degrees of advantages of oil-gas potentials and geological settings.
Proceeding from the evaluation of structural oil-gas deposits,five structural subareas in the Huiming hollow,Shandong,are distinguished:hollow-synclinal limb,anticline-nose-drape structure, stratal onlap-gentle slope zone,fault-steep slope zone,and uplift-rise area.According to a 1 cm×1 cm grid each structural geologic body is quantified.Then a quantification model of oil-gas traps is constructed according to the distribution characteristics of the Sha-3 Member of source and reservoir rocks,T_1-T_r seismic reflection features γ-ray spectrometry and gravity and magnetic analyses,as well as based on the inner relations between the synthetic evaluation indicalors and the known oil-gas deposits.Adaptive Resonance Theory (ART) and Back-Propagation (BP) artificial neural network (ANN) evaluation of oil-gas potentials are made using eighteen indicators such as geologic anomaly values.The high-value favorable regions coincide with the known oil-gas fields.A total of 17 favorable areas for further oil-gas exploration,including 9 first-class and 8 second-class favorable areas, have been delineated according to the degrees of advantages of oil-gas potentials and geological settings.
引文
① 宗国洪,帅德福,王捷等.1995． 济阳坳陷构造特征及有利区带预测.研究报告.胜利油田地质科学研究院.
陈守余,周梅春.1998． 矿产资源预测的ART神经网络方法.中国数学地质9． 北京:地质出版社,73～78．
丁贵明,张一伟,吕鸣岗等.1997． 油气勘探工程.北京:石油工业出版社,132～145．
胡守仁,沈清,胡德文等.1993． 神经网络应用技术.长沙:国防科技大学出版社,42～85．
赵鹏大,李紫金,胡旺亮.1994． 矿床统计预测.北京:地质出版社.
陈守余,周梅春.1998． 矿产资源预测的ART神经网络方法.中国数学地质9． 北京:地质出版社,73～78．
丁贵明,张一伟,吕鸣岗等.1997． 油气勘探工程.北京:石油工业出版社,132～145．
胡守仁,沈清,胡德文等.1993． 神经网络应用技术.长沙:国防科技大学出版社,42～85．
赵鹏大,李紫金,胡旺亮.1994． 矿床统计预测.北京:地质出版社.
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