Distributed Fiber Optic Vibration Signal Logging Well Production Fluid Profile Interpretation Method Research

Author:

Guo Yanan12,Yang Wenming3,Dong Xueqiang2,Zhang Lei3,Zhang Yue3,Wang Yi14,Yang Bo3,Deng Rui1ORCID

Affiliation:

1. Key Laboratory of Oil and Gas Resources and Exploration Technology of Ministry of Education, Yangtze University, Wuhan 430100, China

2. PetroChina Qinghai Oilfield Company, Dunhuang 736202, China

3. PetroChina Tarim Oilfield Company, Korla 841000, China

4. Sinopec Shengli Oilfield Company, Dongying 257100, China

Abstract

Traditional logging methods need a lot of data support such as suction profile information, reservoir geological information, and production information of injection and extraction wells to calculate oil and gas production, which is a tedious and complicated process with low interpretation accuracy. Distributed fiber optic vibration signal logging is a technology that uses fiber optics to sense the vibration signals returned from different formations or well walls to analyze the surrounding formation characteristics or downhole events, which has the advantages of strong real-time monitoring results and high reliability of interpretation results. However, the currently distributed fiber optic vibration signal logging also fails to fully utilize the technical advantages to form a systematic production calculation process. Therefore, this paper proposes to use the K-means++ algorithm to divide the vibration signal frequency bands to represent different downhole events and use the amplitude mean curve envelope area of the reservoir-related frequency bands to calculate the relative production of each production formation. The experimental results correspond well with the relative water absorption data interpreted by conventional production logging, and the accuracy of production interpretation is high, which fills the gap of a production calculation method in the field of distributed fiber optic vibration signal logging in China and strongly promotes the development of the intelligent construction of oil and gas fields.

Publisher

MDPI AG

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