Browsing by Autor "Edgar Camargo"

Now showing 1 - 3 of 3

A First Principles Model for Virtually Sensing Operational Parameters in an ESP Well
(2018) Egner Aceros; Edgar Camargo; José I. Canelón; Alexander Verde
Abstract The main challenges during the operation of electric submersible pumps (ESP) lifted wells include running the well at its optimal point, while honoring operational constraints posed by the production system, and extending the service life of the equipment. Overcoming these challenges will typically require building and continuously updating a model of the system. Now, due to issues such as high cost of sensors (including installation, calibration and maintenance), difficulty to reach the sensing point or lack of adequate technology, measuring some variables may be very hard or even impossible. An alternative is to develop a virtual sensor (model) to estimate unmeasured variables from measured values of other variables at different locations along the well. This work presents a model developed based on physical principles to accurately estimate key operational parameters of ESP lifted wells. The model comprises three differential equations that express the derivatives of pump flowrate, submergence level and well head pressure. Assuming as known the pump frequency, casing head pressure and production line pressure, these equations are solved numerically to estimate time profiles of submergence level, well head pressure, pump flowrate, pump intake pressure, pump discharge pressure and flowing bottomhole pressure. The model was instantiated and simulated for a particular ESP lifted well, and showed outstanding performance when estimating pump intake pressure and pump flowrate, as compared to a commercial simulator. The proposed virtual sensor exhibits high accuracy using a model with simplified equations, which can be executed quickly and reliably using few computational resources (processing time and memory); therefore, this sensor is completely suitable for direct installation in the ESP well (on a PLC or a RTU) for real-time monitoring, control and optimization. Other advantages of the proposed model include that it (i) reduces the required surface and bottomhole instrumentation, (ii) estimates the values of the variables during the transient between operating points, (iii) can be used to analyze the influence of operating parameters in the well behavior, without affecting production rate, (iv) incorporates a service factor to account for the equipment wear due to normal operation and (v) can be used in the implementation of optimization and control strategies.
Análisis de Diagnosticabilidad y Localización de Sensores en un Pozo de Extracción de Petróleo por Inyección de Gas
(2015) José Aguilar; Rubén Leal; Louise Travé-Massuyès; Edgar Camargo; Addison Ríos
Resumen: En este trabajo se propone el uso de un enfoque basado en algoritmos genéticos para obtener relaciones de redundancia de análisis para estudiar la propiedad de diagnosticabilidad en procesos petroleros, y si esta no cumple, nuestro enfoque permite estudiar el problema de localización de sensores con el fin de cumplir con ella. Las relaciones de redundancia se basan en un análisis estructural sobre un grafo bipartito. El análisis de fallas es estudiado usando una función multi-objetivo en varios algoritmos genéticos que describen los diferentes criterios que se deben tratar con el fin de llegar a la propiedad diagnosticabilidad en el sistema. Además, nuestro enfoque permite estudiar el problema de localización de sensores en los sistemas que no cumplen las propiedades de detectabilidad o aislabilidad, usando otro algoritmo genético. Abstract: In this work we propose to use an approach based on genetic algorithms to obtain analytical redundancy relations to study the diagnosability property on oil processes, and if this not fulfill, our approach allows studying the sensor placement problem in order to fulfill it. The redundancy relations are based on a structural analysis over a bipartite graph. The faults analysis is studied using a multi-objective fitness function in several genetic algorithms which describe the different constraints to be covered in order to reach the diagnosability property on the system. Additionally, our approach allows studying the sensors placement problem on systems that do not fulfill the detectability or isolability properties, using another genetic algorithm.
Un modelo de producción de pozos por levantamiento artificial utilizando análisis nodal
(Universidad Autónoma del Estado de México, 2009) Edgar Camargo; L C José Aguilar; Y B Addison Ríos; Ioar Rivas; Joseph Aguilar
"En este trabajo se presenta una técnica para el modelado de la producción en pozos petroleros que requieren levantamie n- to artificial por gas. La técnica está basada en un Análisis Nodal, que permite calcular la relación del flujo d e produ c ción y la caída de presión que ocurrirá en todos los componentes del sistema de la completación. En ese sentido, es posible d e- terminar el flujo de crudo o gas que puede producir un pozo, tomando en cuenta la geometría de la perforación y la co m- plet ación, optimizándose de está manera el sistema de producción y aumentando la tasa de flujo de producción."