重力反演技术在超深层储层预测中的应用——以准噶尔盆地腹部为例  

Application of gravity inversion technology in prediction of ultra-deep reservoirs:A case study of central Junggar Basin

作　　者：陈学国[1] 相鹏[1] 张建华[1] 班丽 吴微 郭涛[1] 冯国志 CHEN Xueguo;XIANG Peng;ZHANG Jianhua;BAN Li;WU Wei;GUO Tao;FENG Guozhi(Exploration and Development Research Institute,Shengli Oilfield Company,SINOPEC,Dongying City,Shandong Province,257015,China)

机构地区：[1]中国石化胜利油田分公司勘探开发研究院,山东东营257015

出　　处：《油气地质与采收率》2024年第4期174-183,共10页Petroleum Geology and Recovery Efficiency

基　　金：中国石化科技攻关项目“准中地区中生界隐蔽圈闭发育模式与精细描述”(P24029)。

摘　　要：准噶尔盆地超深层勘探潜力巨大,应用地震资料进行储层预测是目前油气勘探的主要技术手段,但由于超深层地震资料信噪比低,储-震对应关系不明确,且实钻井少,难以建立有效的地震反演初始模型,这些问题均制约了地震反演技术在超深层储层预测中的应用。重力反演作为一种重要的定量解释手段,可以得到地下的密度分布特征,为地质解释提供支持,根据密度模型可以为地震反演建立相对可靠的低频模型,在一定程度上克服了地震资料在超深层应用的困难,同时重力资料的取得相较于地震资料经济便捷,更易于在实际中应用。因此,提出一种将重力反演应用于地震储层预测的新技术。首先针对重力反演不适定问题,提出基于高斯径向基函数的拟神经网络重力反演技术,提高了重力反演的分辨率和可靠性;其次将重力反演获得的密度模型作为训练数据,与地震和测井数据共同训练神经网络,建立了地震反演的初始模型;最后在初始模型约束下开展地震反演。该技术突破了单一地震资料在超深层储层预测中的应用瓶颈,克服了测井约束的限制,为地震反演提供了可靠的初始模型。应用该技术对准噶尔盆地超深层碎屑岩储层进行预测,结果符合现有地质认识,说明该技术对超深层储层预测具有较高的实用价值和应用潜力,可以为超深层勘探提供技术支持。There is great exploration potential for ultra-deep reservoirs in Junggar Basin,and reservoir prediction with seismic data is the main technical means of oil and gas exploration at present.However,due to the low signal-to-noise ratio of seismic data of ultra-deep reservoirs,unclear reservoir-seismic data correspondence,and few actual drilling wells,it is difficult to establish an ef‐fective initial model for seismic inversion,which restricts the accuracy and reliability of ultra-deep reservoir prediction.Gravity in‐version,as an important quantitative interpretation method,can obtain the characteristics of underground density distribution and provide support for geological interpretation.According to the density model,a relatively reliable low-frequency model can be es‐tablished for seismic inversion,which can overcome the difficulty of applying seismic data in ultra-deep reservoirs to a certain ex‐tent.Meanwhile,the acquisition of gravity data is economical and convenient compared with that of seismic data,and it is easier to be applied in practice.Therefore,a new technique applying gravity inversion to seismic data-based reservoir prediction was devel‐oped in this article.Firstly,a quasi-neural network gravity inversion technique based on Gaussian radial basis functions was pro‐posed to solve the gravity inversion problem and improve the resolution and reliability of gravity inversion.Then,the density body obtained by gravity inversion was used as training data,and a neural network was trained together with seismic and logging data to establish the initial model of seismic inversion.Finally,seismic inversion was carried out with the initial model constraints.This technique broke through the application bottleneck of single seismic data in ultra-deep reservoir prediction and overcame the limita‐tions of logging constraints,providing a reliable initial model for seismic inversion.The application of this technique to the predic‐tion of ultra-deep clastic rock reservoirs in Junggar Basin was consist

关 键 词：重力反演 联合反演 神经网络 超深层 储层预测 准噶尔盆地 

分 类 号：TE357[石油与天然气工程—油气田开发工程]