Application of Fuzzy Logic in Selection of Best Well for Hydraulic Fracturing in Oil and Gas Fields

  • T. Sh. SalavatovEmail author
  • Khurram Iqbal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1095)


To meet high demand of hydrocarbons, innovative techniques are imperative, therefore hydraulic fracturing become popular to extract hydrocarbons from shale and tight formations. Designing of treatment and selection of most appropriate well for hydraulic fracturing plays a vital role to achieve maximum benefit from this expensive technology. Designing hydraulic fracturing job initiates with identification of best candidate well for job which includes understanding geological factors of area, well location, lithology, selection of proppant volume and understanding of created fracturing geometry, proppant volume. Other main constituents are fracture geometry which includes fracturing length, height and width.

Fuzzy Logic Systems application is vastly used in research area of petroleum engineering. This paper is focused on using fuzzy logic technique to decide best well for best well for hydraulic fracturing. Selection of most suitable well for hydraulic fracturing, among many zones/layers within many numbers of producing wells is reflected makes it difficult, especially when the selection process depends upon on a group of parameters having different variables, attributes and features. This process becomes multifaceted, nonlinear and advocate with uncertainties. This technique is proved to reduce uncertainties in selection of most suitable well for stimulation and hydraulic fracturing.

In the end of this paper example is also provided where fuzzy logic was used to reduce the uncertainties and by selecting the best candidate well, hydrocarbons (gas) production of candidate well was increased four times of its natural ability by using fuzzy logic.


Hydraulic fracturing Fuzzy logic Well selection 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Petroleum EngineeringAzerbaijan State Oil and Industrial UniversityBakuAzerbaijan
  2. 2.Dewan Petroleum LimitedIslamabadPakistan

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