eprintid: 17360
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/73/60
datestamp: 2023-12-19 03:23:45
lastmod: 2023-12-19 03:23:45
status_changed: 2023-12-19 03:07:55
type: article
metadata_visibility: show
creators_name: Umar Ibrahim, A.
creators_name: Mamo Negash, B.
title: Shale Gas Productive Volume Optimization
ispublished: pub
keywords: 3D modeling; Forecasting; Fracture; Gases; Geometry; Hydraulic fracturing; MATLAB; Natural gas well production; Natural gas wells; Petroleum reservoirs; Shale gas, 3D models; 3d-modeling; Fracture geometries; Fracture height; Fracture width; Gas well; Shale gas reservoirs; Simple++; Stimulated reservoir volumes; Volume optimisation, Productivity
note: cited By 0; Conference of 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 ; Conference Date: 17 December 2020 Through 18 December 2020; Conference Code:286319
abstract: Recently, a modified mathematical model was presented in order to determine the productivity of multi-fractured shale gas wells. However, the considerable challenge of the model was assuming an average fracture width for the determination of the practical fracture geometry of the stimulated reservoir volume. This challenge led to over prediction of the gas well. Therefore, this paper presents a simple and accurate method using a pseudo-3D model to determine the fracture width in shale gas reservoirs. The method utilized the hydraulic fracturing propagation capacity of the MATLAB software to visualize the fracture geometry, which includes the fracture height, fracture length, and the fracture width. So, the obtained fracture width can be incorporated with analytical models to predict long term productivity for multistage fractured shale gas wells. An accurate result for the productivity will assist in determining the ultimate gas recovery, propped volume, optimal fracture length, fracture spacing and predict the future performance of the well. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
date: 2022
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142770625&doi=10.1007%2f978-981-16-2183-3_10&partnerID=40&md5=c3586507fcd87e1a9549cb145082ad04
id_number: 10.1007/978-981-16-2183-3₁₀
full_text_status: none
publication: Lecture Notes in Electrical Engineering
volume: 758
pagerange: 117-123
refereed: TRUE
isbn: 9789811621826
issn: 18761100
citation:   Umar Ibrahim, A. and Mamo Negash, B.  (2022) Shale Gas Productive Volume Optimization.  Lecture Notes in Electrical Engineering, 758.  pp. 117-123.  ISSN 18761100