A web-based expert system for the planning and completion of multilateral wells

Garrouch, Ali A.; Lababidi, Haitham M.S.; Ebrahim, Abdullah S.

doi:10.1016/j.petrol.2005.05.009

Cited by 13 publications

(4 citation statements)

References 30 publications

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“…However, fuzzy logic is most often used in combination with other artificial intelligence methods. For example, an expert system developed by Garrouch et al [3] uses the theory of fuzzy sets to plan the shape and equipment of multilateral wells.…”

Section: Application Of Artificial Intelligence Methods In the Oil Anmentioning

confidence: 99%

Intelligent control of CO₂-EOR process

Mikolajczak¹,

Stopa²,

Wojnarowski³

et al. 2018

drill

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Section: Application Of Artificial Intelligence Methods In the Oil Anmentioning

confidence: 99%

Intelligent control of CO₂-EOR process

Mikolajczak¹,

Stopa²,

Wojnarowski³

et al. 2018

drill

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“…It follows a systematic approach, first screening for horizontal and multilateral candidates, if applicable then what completion type of the lateral section and then what junction levels. The developed system was tested on eight oil field cases collected from literature and successfully provided recommendations that were consistent with reality (Garrouch, et al, 2005).…”

Section: Petroleum Engineering Applications Of Artificial Expert Systemsmentioning

confidence: 96%

Development and Utilization of Integrated Artificial Expert Systems for Designing Multi-Lateral Well Configurations, Estimating Reservoir Properties and Forecasting Reservoir Performance

Al-Mousa

Ertekin

2013

Day 2 Tue, October 29, 2013

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Reservoir simulation is one of the main tools if not the most important one reservoir engineers use to forecast a reservoir performance. Nevertheless, developing and operating a reservoir simulator in the first place can be an arduous task that requires a set of highly skilled individuals in science, advanced mathematics, programing, and reservoir engineering and powerful computational models. v Table of Contents List of Figures .

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“…Among AI techniques, the expert system plays a crucial role in combining expert knowledge with self-learning algorithms. Garrouch et al [18] introduced a web-based fuzzy expert system for preliminary planning and completion of a multilateral well.…”

Section: State-of-the-art In Multilateral Well Placement Optimizationmentioning

confidence: 99%

End-Point Model for Optimization of Multilateral Well Placement in Hydrocarbon Field Developments

et al. 2020

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Drilling cost is one of the most critical aspects in the reservoir management plan. Costs may exceed a million dollars; thus, optimal designing of the well trajectory in the reservoir and completion are essential. The implementation of a multilateral well (MLW) in reservoir management has great potential to optimize oil production. The object of this study is to develop an integrated workflow of end-point multilateral well placement optimization integrated with the reservoir simulator supported by artificial intelligence (AI) methods. The paper covers various types of MLW construction, including: horizontal, bi-, tri-, and quad-lateral wells. For quad-lateral wells, the capital expenditure is highest; nevertheless, acceleration of oil production affects the project’s NPV (net present value), indicating the type of well that is most promising to implement in the reservoir. Tri- and quad-lateral wells can operate for 12.1 and 9.8 years with a constant production rate. The decreasing hydrocarbon production rate is affected by reservoir pressure and the reservoir water production rate. Other well design patterns can accelerate water production. The well’s optimal trajectory was evaluated by the genetic algorithm (GA) and particle swarm optimization (PSO). The major difference between the GA and PSO optimization runs is visible with respect to water production and is related to the modification of one well branch trajectory in a reservoir. The proposed methodology has the advantage of easy implementation in a closed-loop optimization system coupled with numerical reservoir simulation. The paper covers the solution background, an implementation example, and the model limitations.

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A web-based expert system for the planning and completion of multilateral wells

Cited by 13 publications

References 30 publications

Intelligent control of CO₂-EOR process

Intelligent control of CO₂-EOR process

Development and Utilization of Integrated Artificial Expert Systems for Designing Multi-Lateral Well Configurations, Estimating Reservoir Properties and Forecasting Reservoir Performance

End-Point Model for Optimization of Multilateral Well Placement in Hydrocarbon Field Developments

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