多孔性
中子
分辨率(逻辑)
测井
功能(生物学)
基质(化学分析)
油田
计算机科学
石油工程
材料科学
物理
地质学
岩土工程
核物理学
人工智能
生物
进化生物学
复合材料
出处
期刊:
[Elsevier BV]
日期:2023-04-17
卷期号:226: 211783-211783
被引量:3
标识
DOI:10.1016/j.geoen.2023.211783
摘要
In the later stages of oilfield development, the accurate identification of thin reservoirs become increasingly crucial for oil and gas exploration. However, conventional logs have limited vertical resolution, making it challenging to identify thin reservoirs. This results in potential hydrocarbon layers getting overlooked during exploration. To address this issue, a novel resolution enhancement method for density and neutron porosity logs based on physical constraint optimization is proposed. The proposed method involves three main steps: (1) developing an objective function that relates the true formation density and porosity to the measurement based on the physics of nuclear, (2) setting density neutron cross-constraints using the volumetric model of logging interpretation, and (3) establishing the objective function matrix equations using sliding window technology and solving the matrix equations using the constrained least square method to obtain high-resolution density and neutron porosity logs. The proposed method is evaluated using both synthetic and field logs obtained from compensated density and compensated neutron tools. The results demonstrate an effective improvement in neutron porosity and density log resolution to 15 cm, which is significantly enhanced compared to the typical vertical resolution of 2 ft. This study offers a new perspective for enhancing the resolution of logs and contributes to the exploration and development of thin oil and gas resources. And the proposed method could be used in future exploration and production projects to identify potential hydrocarbon layers that might have been overlooked by conventional logs.
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