An Innovative Method: Risk Assessment for Exploration and Development of Oil and Gas

Chang, Yu Web; Dou, Haiyang; Chen, Changchun; Wang, Xiaolin; Liu, Kun

doi:10.2118/104458-ms

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…Several specialized journals have also published numerous articles dedicated to the approach of problems through the AHP in areas like Socio-Economic Planning Sciences, Mathematical Modeling and Operations Research, among others. Only the brief but helpful explanations of Chang et al [16], and reservoir planning applications of Gerbacia et al [17], have been put in working models that aid the decision making process at different scales and levels of importance.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

Mohanty¹,

Roy²,

Ganguly³

et al. 2019

IJITEE

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Risk assessment has become essential tool for construction of project in a safe and secure manner. In this paper, one of the Multi-Criteria Decision-Making (MCDM) method is used i.e. AHP (Analytic Hierarchy Process) to rank the investment alternatives from a risk point of view, by taking into consideration the preferences of the investor or decision maker. The proposed approach not only involve identification of potential risks but also analyze the risks and mitigate them, so that it can lead to the overall success of a project.

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Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

Mohanty¹,

Roy²,

Ganguly³

et al. 2019

IJITEE

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“…Fuzzy logic helps to guarantee precision and quality and to avoid inconsistency and uncertainty (Bilgen, 2010). Fuzzy logic applications in E&P operations have been reported in different areas such as engineering design and control (Nikravesh et al 1997;Sengul and Bekkousha 2002;Mohaghegh et al 2005;Widarsono et al 2005;Cao et al 2006;Taheri 2008;Weiss et al 2001;Zarei et.al. 2008;Murillo et al 2009) and also in operations of production facilities, systems and optimal well operations (Rivera and Farabee 1994;Dumans 1995;Xiong et al 2001;Alimonti and Falcone 2004;Garrouch and Lababidi 2005)…”

Section: Application Of Fuzzy Logic In Eandpmentioning

confidence: 99%

A review of fuzzy logic applications in petroleum exploration, production and distribution operations

Okwu

Nwachukwu

2018

J Petrol Explor Prod Technol

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Petroleum exploration and production business thrives with in-depth knowledge and understanding of the subsurface. Technological advancement has helped in furnishing the industry with much information about the petroleum reservoir; however, a lot of uncertainties still exist due to the nature of the subsurface. The industry has strived to address this problem in diverse ways; regrettably, the classical methods relied upon have failed to provide a proper guide to management decision in exploiting these reservoirs. In recent times, artificial intelligence techniques, particularly Fuzzy Logic (FL), have been identified as a potential tool to deal with the uncertainties encountered in most exploration and production (E&P) operations. This research provides a review of FL applications in E&P operations under non-deterministic input parameters, possible challenges and solution procedures using FL sensitivity analysis and rule viewers. The focus is on reservoir characterization for reservoir evaluation, drilling/completion operations and stimulation treatment. The study also examines the extent FL could be applied to extract useful information from the large volume of historical oil and gas data already on the shelf and the future gaps to fill. A case study was presented which considered cost optimization in Liquefied Petroleum Gas (LPG) distribution operations using fuzzy logic.

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“…Recently, fuzzy-logic systems have been used to solve a number of different problems in a variety of areas, including physical and chemical systems, production planning and scheduling, location and transportation problems, resource allocation in financial systems, and engineering design. In the petroleum industry, fuzzy logic has been put to work in many different areas since the early 1990s, including reservoir characterization (Hambalek and Gonzalez 2003;Lim and Kim 2004;Rafiei et al 2009;Shokir 2006;Soto et al 2001;Taghavi 2005;Zhou et al 1993;Cuddy 2000;Kedzierski and Mallet 2006;Finol et al 2002;Hajizadeh 2007a), optimal well operations (Alimonti and Falcone 2004; Lababidi 2003, 2005;Rivera 1994;Dumans 1995;Xiong et al 2001), stimulation treatment (Xiong and Holditch 1995;Nitters et al 2000), and economic analysis (Zolotukhin 2000;de Salvo Castro and Fereira Filho 2001;Agbon and Araque 2003;Chang et al 2006). An extensive list of such applications is presented in Table 1.…”

Section: Introductionmentioning

confidence: 99%

“…† Sengul and Bekkousha (2002); Mohaghegh et al (2005); Widarsono et al (2005); Nikravesh et al (1997); Taheri (2008); Weiss et al (2001); Cao et al (2006); Zarei et al (2008); Wu et al (1997); Murillo et al (2009); Kanj and Roegiers (1999); Hajizadeh (2007b); Garrouch and Al-Ruhaimani (2003). † † Zolotukhin (2000); de Salvo Castro and Fereira Filho (2001); Agbon and Araque(2003);Chang et al (2006).…”

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confidence: 99%

Production-System Optimization of Gas Fields Using Hybrid Fuzzy/Genetic Approach

Park¹,

Lim²,

Roh³

et al. 2010

SPE Journal

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The design of production systems of gas fields is a difficult task because of the nonlinear nature of the optimization problem and the complex interactions between each operational parameter. Conventional methods, which are usually stated in precise mathematical forms, cannot include the uncertainties associated with vague or imprecise information in the objective and constraint functions.This paper proposes a fuzzy nonlinear programming approach to accommodate these uncertainties and applies it to a variety of optimization processes. Specifically, the fuzzy -formulation is combined with a hybrid coevolutionary genetic algorithm for the optimal design of gas-production systems. Both the multiple conflicting objective and constraint functions for production systems of gas fields are formulated in a feasible fuzzy domain. Then, the genetic algorithm is used as a primary optimization scheme for solving the optimum gas-production rates of each well and the pipeline segment diameters to minimize the investment cost with a given set of constraints in order to enhance the ultimate recovery.The synthetic-optimization method can find a global compromise solution and offer a new alternative with significant improvement over the existing conventional techniques. The reliability of the proposed approach is validated by a synthetic practical example yielding more-improved results. This method constitutes an offering of a powerful tool for cost savings in the planning and optimization of gas-production operations.

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An Innovative Method: Risk Assessment for Exploration and Development of Oil and Gas

Cited by 9 publications

References 10 publications

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

A review of fuzzy logic applications in petroleum exploration, production and distribution operations

Production-System Optimization of Gas Fields Using Hybrid Fuzzy/Genetic Approach

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