Loss Analysis and Diagnosis Based on Natural Language Processing and Big Data Analysis

ZENG Yijin; LI Daqi; CHEN Zengwei; ZHANG Dujie; CUI Yahui; ZHANG Feifei

doi:10.11911/syztjs.2023108

Volume 51 Issue 6

Nov. 2023

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Petroleum Drilling Techniques > 2023 > 51(6): 1-11. > DOI: 10.11911/syztjs.2023108

ZENG Yijin, LI Daqi, CHEN Zengwei, et al. Loss analysis and diagnosis based on natural language processing and big data analysis [J]. Petroleum Drilling Techniques，2023, 51(6)：1-11. DOI: 10.11911/syztjs.2023108

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Loss Analysis and Diagnosis Based on Natural Language Processing and Big Data Analysis

ZENG Yijin^{1, 2,},
LI Daqi^{1, 2,*, ,},
CHEN Zengwei^{1, 2},
ZHANG Dujie^{1, 2},
CUI Yahui³,
ZHANG Feifei³

1.
State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Beijing, 102206, China
2.
Sinopec Research Institute of Petroleum Engineering Co., Ltd., Beijing, 102206, China
3.
Hubei Key Laboratory of Drilling and Production Engineering for Oil and Gas(Yangtze University), Wuhan, Hubei, 430100, China

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Received Date: November 16, 2022
Revised Date: November 12, 2023
Available Online: November 21, 2023

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Abstract

Abstract

The Block A in the western part of the Tarim Basin are mainly karst-vuggy and fractured reservoirs. Eighteen fault zones are developed in the block. The natural fractures located near the fault zones have complex distribution and low bearing capacity of the formation, which are prone to lost circulation. In order to accurately avoid the risk of lost circulation and optimize the technical measures to deal with the lost circulation, natural language processing technology was used to extract all the drilling and completion data and lost circulation information of Block A. Based on big data analysis, the uncertainty distribution of the equivalent density of the actual formation pressure and the actual fracture pressure in the leaky formation was summarized. The uncertainty range of fracture development and fracture width, as well as the lost circulation risk coefficient of the leaky formation were calculated, and the pre-drilling lost circulation risk diagnosis method was established. The case analysis showed that the proposed method could be used to diagnose the risk of lost circulation before drilling, which can provide a basis for avoiding the risk of lost circulation and developing the technical measures for lost circulation treatment during drilling and completion.
- natural language processing,
- big data,
- loss diagnosis,
- equivalent circulating density,
- degree of fracture development

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References

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