LITHOLOGY AND RESERVOIR IDENTIFICATION IN THE “EL” WELL, EAST JAVA USING SEISMIC INVERSION

Maulana Yusuf Ibrahim, Salma Dita Rysqi Puspita, Z. Syarafina, S. Zulivandama, E. Agustine
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Abstract

The acoustic impedance inversion seismic method, carried out at the "EL" well in East Java,provides a description of the physical properties of subsurface rocks. This method involves identifying rocklayers, lithology types, porosity values, the presence of hydrocarbons, and fluids in the target zone usingboth well data and integrated seismic data. The data processing included the cross-plotting of acousticimpedance (AI) with gamma ray logs, porosity logs, and resistivity logs. We integrated seismic and welldata, picked horizons, and created AI inversion models. The based model inversion technique was used tocompare the synthetic model with the seismic data, aiming to obtain an AI value that closely represents theactual model. AI seismic inversion effectively separates lithological boundaries vertically and laterally,based on the selected picking horizon and created model. To enhance understanding of the lithology andhydrocarbon prospect zone in the study area, a cross-plot analysis was used to correlate the seismic inversionmodel. The results reveal that the study area represents a hydrocarbon prospect zone, with reservoir rocksconsist of coral and foram at a depth range of 2320 - 2430 ft.
东爪哇el井岩性及储层反演识别
在东爪哇的“EL”井进行的声阻抗反演地震方法描述了地下岩石的物理性质。该方法包括使用井数据和综合地震数据识别目标区的岩层、岩性类型、孔隙度值、碳氢化合物的存在和流体。数据处理包括声阻抗(AI)与伽马射线测井、孔隙度测井和电阻率测井的交叉绘图。我们整合了地震和油井数据,选择了层位,并创建了人工智能反演模型。采用基于模型反演技术将合成模型与地震数据进行比较,旨在获得一个与实际模型最接近的AI值。人工智能地震反演在选择拾取层位和建立模型的基础上,有效地从纵向和横向分离了岩性边界。为了加深对研究区岩性和油气远景带的了解,采用了交会图分析法对地震反演模型进行了关联。研究结果表明,研究区是一个油气远景区,储层岩石由珊瑚和有孔虫组成,深度范围为2320-2430英尺。
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16 weeks
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