The development of informational and analytical system for wells monitoring and control (for Almetyevneft Oil and Gas Production Department)

Oleg .V. Denisov TatASU Almetyevsk, Russian Federation denisovov@asu.tatneft.ru
Ruslan G. Girfanov TatASU Almetyevsk, Russian Federation girfanov_r@tatneft.ru
Alexandra V. Kuzmina TatASU Almetyevsk, Russian Federation kuzminaav@asu.tatneft.ru
The article describes basic directions of the development and implementation of informational and analytical system of wells monitoring and control for Almetyevneft Oil and Gas Production Department.The approaches for evaluation of the wells interference on the basis of telemetry data analysis (identification of parameters fora simplified system of material balance equations, neural-network analysis) are presented, the using of the neural network method in the implementation of the non-stationary flooding is proposed, the block-diagram of system is shown. The article gives the method to localize sections with greatest hydrodynamic connection and demonstrates the use of computer-aided analysis of data in the problem of setting of well behavior.
Materials and methods
Method of wells interference estimating andmethod of flooding pattern selection based on neural network algorithms.
Results
Basic directions of the development and implementation of informational and analytical system for wells monitoring and control(for Almetyevneft Oil and Gas Production Department) are presented. The article gives the approaches for evaluation of the wells interference and solutions to well behavior selection problem.
Сonclusions
Implemented methods of wells interference evaluating are characterized by:
• Identification based on the simplified system of material balance equations - high computational cost, proximity to the classical approaches in modeling;
• neural network algorithms - high speed,suitability for a wide range of applications;
• heuristics algorithms providing a qualitative assessment of interference, high speed.The article gives:
• method to localize sections with greatesthydrodynamic connection;
• method to implement the subsystem to monitor functioning of wells with non-stationary wateflooding;• demonstration of the neural network data analysis potential in the task of behaviorselecting during non-stationary waterflooding;
• method to analyze the potential of area touse of a particular behavior.
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information system oil and gas field management wells interference non-stationary water-flooding