Hybrid intelligent supervision model of oil wells

Camargo, Edgar; Aguilar, José

doi:10.1109/fuzz-ieee.2014.6891725

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…It shows the learning results for the anger emotion in the same context. List of existing relationships -----------------------------------ID: 1 Changed values: [11,97080110770,208201,10] Column of values [4,5,7,8]…”

Section: Results Of Our Learning Algorithmmentioning

confidence: 99%

“…The second is based on a fuzzy system of rules of type IF <Condition> THEN <Action>, which defines the control actions according to the conditions of the problem that are fulfilled in a given time. In particular, a Multilayer Diffuse Classifier System [5] was used, that consist of a series of fuzzy systems of rules connected hierarchically. In this case, we compare the learning capability of these three techniques.…”

Section: E Comparison With Other Workmentioning

confidence: 99%

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An approach for the structural learning of chronicles

Aguilar¹,

Aguilar²,

Mesa³

2018

ces

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The Chronicles are patterns characterized by observable events, with temporal relationships between them. In this work, we propose a model for the building of chronicles, through a learning strategy that allows defining its structure. Our approach discovers the events that compose a chronicle and the temporal relationships between them. These events are defined by changes in the descriptors/features of the modeled phenomena, according to the sequence in which they appear. We test our approach for modeling a hierarchical pattern of vehicle driving styles, which consists of three levels, one to describe the emotional states, another to describe the driver states and, finally, the last one to describe the driving styles. Finally, our approach is compared with other techniques, in classical benchmark classification problems.

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Section: Results Of Our Learning Algorithmmentioning

confidence: 99%

Section: E Comparison With Other Workmentioning

confidence: 99%

An approach for the structural learning of chronicles

Aguilar¹,

Aguilar²,

Mesa³

2018

ces

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“…Our HIS is composed by a MFCS and a GA [10]. The MFCS consists of a number of fuzzy sys-219 ADVANCED SUPERVISION OF OIL WELLS .…”

Section: Hybrid Intelligent Systemsmentioning

confidence: 99%

“…Our HIS is composed by a MFCS and a GA [10]. The MFCS consists of a number of fuzzy systems hierarchically distributed, which allows identifying the different operational scenarios present in the oil production process.…”

Section: Hybrid Intelligent Systemsmentioning

confidence: 99%

“…The utilization of Hybrid Intelligent Systems (HIS) on supervision tasks in production systems is becoming an area of great interest at industrial level [1], [3], [5], [10]. Particularly, the HIS have gained a large influence in the oil industry, because they allow approaching the problem of handling the complexity of the hydrocarbon production systems [1], [2].…”

Section: Introductionmentioning

confidence: 99%

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Advanced Supervision Of Oil Wells Based On Soft Computing Techniques

Camargo

Aguilar

2014

Journal of Artificial Intelligence and Soft Computing Research

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In this work is presented a hybrid intelligent model of supervision based on Evolutionary Computation and Fuzzy Systems to improve the performance of the Oil Industry, which is used for Operational Diagnosis in petroleum wells based on the gas lift (GL) method. The model is composed by two parts: a Multilayer Fuzzy System to identify the operational scenarios in an oil well and a genetic algorithm to maximize the production of oil and minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production. Additionally, the first layers of the Multilayer Fuzzy System have specific tasks: the detection of operational failures, and the identification of the rate of gas that the well requires for production. In this way, our hybrid intelligent model implements supervision and control tasks.

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