Preliminary study on the recognition of flowback characteristics after exploration and evaluation of ultra-deep oil and gas Wells

Abstract The oil and gas reservoirs in the Tarim Basin are generally buried deep, and more than 90% of the oil and gas wells are ultra-deep wells. The oil testing and completion operations of ultra-deep wells have four major characteristics: “high”, “deep”, “connected” and “complex”. At the same time, the operation risks are high, the well construction cycle is long, the natural productivity is low, and the stable production is difficult. More than 70% of the wells require reservoir transformation. The blowout production cycle after the transformation is long. The return flow data obtained at the cost of huge time and money fails to provide sufficient information for subsequent production guidance. This paper proposes a method for studying the characteristics of reservoir return flow based on the analysis of blowout production data. Two new parameters, the decline ratio and the return flow ratio, are defined. The return flow ratio versus decline ratio curve can be used to analyze reservoir physical properties and heterogeneity, and can be used to effectively predict formation water production in combination with the water property data of the return flow fluid. This method improves the utilization rate of return flow data, can help guide the subsequent blowout production process, shorten the time for blowout production, save time and money, and improve the efficiency of oil testing operations.

Authors

Institutions

Publication Details

Journal
Journal of Physics Conference Series
Published
2025-09-01
DOI
https://doi.org/10.1088/1742-6596/3048/1/012120
Primary Topic
Hydraulic Fracturing and Reservoir Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preliminary study on the recognition of flowback characteristics after exploration and evaluation of ultra-deep oil and gas Wells

Feng Shan, Zhenjiang Wu, Fumin Li, Shun Lei et al.
Journal of Physics Conference Series
Hydraulic Fracturing and Reservoir Analysis
article

Preliminary study on the recognition of flowback characteristics after exploration and evaluation of ultra-deep oil and gas Wells

Feng Shan, Zhenjiang Wu, Fumin Li, Shun Lei, Kun Zhang, Hao Wang, Hongqiang Zhang, Dan Wang
article en

Abstract

Abstract The oil and gas reservoirs in the Tarim Basin are generally buried deep, and more than 90% of the oil and gas wells are ultra-deep wells. The oil testing and completion operations of ultra-deep wells have four major characteristics: “high”, “deep”, “connected” and “complex”. At the same time, the operation risks are high, the well construction cycle is long, the natural productivity is low, and the stable production is difficult. More than 70% of the wells require reservoir transformation. The blowout production cycle after the transformation is long. The return flow data obtained at the cost of huge time and money fails to provide sufficient information for subsequent production guidance. This paper proposes a method for studying the characteristics of reservoir return flow based on the analysis of blowout production data. Two new parameters, the decline ratio and the return flow ratio, are defined. The return flow ratio versus decline ratio curve can be used to analyze reservoir physical properties and heterogeneity, and can be used to effectively predict formation water production in combination with the water property data of the return flow fluid. This method improves the utilization rate of return flow data, can help guide the subsequent blowout production process, shorten the time for blowout production, save time and money, and improve the efficiency of oil testing operations.

Journal of Physics Conference SeriesVol. 3048(1)
Tarim University (CN), Cosmo Oil (Japan) (JP)
Openalex Percentile: Top 75%
Hydraulic Fracturing and Reservoir Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Preliminary study on the recognition of flowback characteristics after exploration and evaluation of ultra-deep oil and gas Wells — Feng Shan, Zhenjiang Wu, et al. · Journal of Physics Conference Series (2025) | TGRS Research Map | TGRS