Evaluating production behaviour of CBM wells from Raniganj Coalfield through reservoir characterization under constrained field data conditions

Chattaraj, Sujoy; Upadhyay, Rajeev; Mohanty, Debadutta; Halder, Gopinath; Kumar, T. Santhosh

doi:10.1016/j.jngse.2021.103969

Cited by 14 publications

(10 citation statements)

References 38 publications

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“…Taking CBM as an example, , this paper introduces the detailed application method of the data lake. The data lake still has broad application prospects in other fields of the petroleum industry, − and the reasons are as follows: − master data management module: With the deepening of the construction of the data lake, the petroleum exploration industry is gradually trying to use the advantages of the data lake to carry out data governance. The master data management module of the data lake is mainly used to manage the master data information of the data lake.…”

Section: Application Prospectsmentioning

confidence: 99%

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Wang¹,

Adenutsi

Wang³

et al. 2023

ACS Omega

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With the rapid development and widespread application of big data and artificial intelligence, the upgrading of digital and intelligent industries has been rapidly popularized in the oil and gas industry. First, based on the theory of ″regional data lake″, the digital nature of the CBM governance system is analyzed, and the optimization model of CBM governance for different data types is established. Second, considering the geological characteristics and development mode of the CBM reservoir, the regional data lake expansion model is established. Third, a theoretical model of coupling ″on-site data, laboratory data, management data, and data management system″ has been established. The research shows the following: (a) The CBM governance system based on the regional data lake can be divided into four parts: basic support, data life cycle, core governance areas, and governance strategy support. (b) The coupling of the coalbed methane governance model with the BP neural network model in this article has good application results. (c) The computational efficiency of this model has been improved by 12%, which has broad application prospects.

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Section: Application Prospectsmentioning

confidence: 99%

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Wang¹,

Adenutsi

Wang³

et al. 2023

ACS Omega

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“…Injection/fall-off is one of the commonly used methods in CBM well testing at present. 31 In this study, according to the Chinese national standard method of injection/falloff well testing for coalbed methane wells (GB/T 24504-2009), the parameters of target coal-seam permeability, investigation radius, skin factor, and reservoir pressure of the CBM wells in the study area were calculated. The expressions are as shown in the following equations:…”

Section: Injection/fall-off Testsmentioning

confidence: 99%

Impact factors and contributions of commingled production in multiple coal seams

Jin

Fang

et al. 2022

Energy Science & Engineering

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The multilayer development of coalbed methane (CBM) is affected by many factors, and the gas production contribution of each seam is unclear. In this study, 12 geological and 10 engineering parameters were adopted to reveal the key factors affecting the combined-layer drainage productivity of CBM wells before using numerical simulation to clarify the contribution of each coal seam. The results show that the coal reservoir in the Laochang mining area exhibited the advantages of high gas content, intact coal body structure, and large thickness of the combined coal seams, and it was deficient with low saturation and ratio of critical desorption pressure to reservoir pressure. The medium permeability after fracturing and the influence of a small range of fracturing leads to the steep and deep pressure drop funnel of the coal reservoir, and most of the reservoir pressure drop is ineffective; this may be the reason for the unstable production and rapid attenuation of most CBM wells in the study area. The gas production of the Nos. 13 and 18 coal seams is stable and makes a significant contribution, and they can be used as the key objects of follow-up CBM exploration and development in this area. Geological factors, such as coal body structure, ratio of critical desorption pressure to reservoir pressure, thickness of combined coal seams, and gas saturation, as well as engineering factors, such as permeability and half length of fractures after fracturing, are the main factors affecting the productivity of the CBM wells in the Laochang mining area.

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“…Therefore, CBM Company has firmly established the concept of “deep overburden, high quality and dense, shallow and deep plowing, shale research, developing new fields, breaking through the periphery, empowering cooperation, expanding new energy (sources), and digital management.” Based on the above strategic objectives, CBM has extensively studied the integration of geology and gas engineering technologies and their application prospects in the field of geological and gas reservoir engineering. − Baker Hughes’ integrated geology and engineering research platform integrates three major software packagesgeological modeling, geomechanical modeling, and fracturing softwareinto one integrated geological engineering research platform. − It realizes from seismic data interpretation, structural modeling, three-dimensional (3D) geological modeling, and 3D geomechanical modeling. − It is used for drilling optimization design, engineering fracturing application, and reservoir numerical simulation. Based on (open group open subsurface data universe) OSDU’s upstream data management platform, Schlumberger’s DELFI Geological Integrated Research Environment integrates a range of native cloud applications into Petrel’s specialized software core. − It enables integrated studies of exploration, geology, modeling, numerical simulation, well completion, and production. Based on the special characteristics of deep CBM reservoirs, traditional technical methods such as sweet spots prediction, well logging evaluation, geological modeling, and optimization of fracturing engineering parameters can no longer meet the requirements .…”

Section: Introductionmentioning

confidence: 99%

Intelligent Decision-Making System for Integrated Geological and Engineering of Deep Coalbed Methane Development

Wang,

Huang

et al. 2023

Energy Fuels

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Coalbed methane (CBM) exploration and development is becoming increasingly complex, and the deterioration of resource quality is intensifying. In this paper, first, based on the research results of data regional lake and fine description of gas reservoirs, artificial intelligence technology was applied to deep mining and analysis of comprehensive data of CBM reservoirs. Second, an innovative integrated CBM geology engineering intelligent decision-making system based on big data analysis algorithms was developed. Third, the fast single-well production prediction and master controlling factor analysis driven by big data is achieved. Fourth, comprehensive sweet spot analysis was conducted on CBM reservoirs by combining geological and engineering factors. The fracturing parameters based on the analysis of the main control factors of production after fracturing of CBM wells were optimized. The system is promoted and applied in Daning block on the east edge of the Ordos Basin. Results show that (a) the system has significantly improved the efficiency of gas reservoir research and the effectiveness of engineering decisions, and (b) it provides a powerful new method and system support for fully understanding the resource potential of gas reservoirs and comprehensively promoting the deep application of intelligence in scientific research and production.

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Evaluating production behaviour of CBM wells from Raniganj Coalfield through reservoir characterization under constrained field data conditions

Cited by 14 publications

References 38 publications

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Impact factors and contributions of commingled production in multiple coal seams

Intelligent Decision-Making System for Integrated Geological and Engineering of Deep Coalbed Methane Development

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