Improved Permeability Estimation: From Static to Dynamic To Understand Productivity Better
- Wang Xiannan (CNOOC Shenzhen) | Xiao Dong (CNOOC Shenzhen) | Guan Lijun (CNOOC Shenzhen) | Gao Bei (Schlumberger) | Cai Huimin (Schlumberger) | Shim Yen Han (Schlumberger) | Qu Changwei (Schlumberger)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- SPWLA 25th Formation Evaluation Symposium of Japan, 25-26 September, Chiba, Japan
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petrophysicists and Well Log Analysts
- 6 in the last 30 days
- 53 since 2007
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Permeability is a measure of the rock’s ability to allow the fluid flow. This rock ability is not only related to the pore throat size and distribution, which is absolute permeability or intrinsic permeability; but also, it manifests the flow ability of different fluids to move through the pore space, which is effective permeability. When to evaluate productivity during exploration stage, the general practice is often focus on the intrinsic permeability estimation from LWD logs or Wireline logs, or core analysis, but effective permeability and its inter-relationship to intrinsic permeability has been overlooked; the result therefore can lead to the big error for production prediction in the early stage of life cycle, especially in complex reservoir system, such as heterogeneity and low permeability formations etc., consequently impact the decision-making process of completion schemes, and development plans.
This paper delivered a comprehensive workflow of permeability evaluation, that is to integrate resistivity ratio clusters, logging facies and lithofacies classification based on open-hole logs and core data to identify rock types and build an intrinsic permeability model; then use wireline formation tester (WFT) mobility, WFT flowing mobility and WFT pressure-transient-analysis (PTA) to quantify effective permeability, and establish a relationship between intrinsic permeability and effective permeability; Lastly, delivered improved reservoir quality index (RQI) and productivity index (PI) for the formation evaluation in an exploration well. The result was used not only to optimize the drill stem test, but also it showed the good match with DST, and provided the general practice in this field for later well correlations.
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