DEVELOPMENT OF A PRODUCTION DATA ANALYSIS MODEL AND ITS APPLICATION IN A PRODUCING OIL RESERVOIR

Open Access
Author:
Yue, Wenting
Graduate Program:
Energy and Mineral Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
October 31, 2016
Committee Members:
  • John Yilin Wang, Dissertation Advisor
  • John Yilin Wang, Committee Chair
  • Turgay Ertekin, Committee Member
  • Li Li, Committee Member
  • Steven Greybush, Outside Member
Keywords:
  • production data analysis
  • Ensemble Kalman Filter
  • Whole-field evaluation
  • Reservoir simulation
  • history matching
Abstract:
Production data analysis (PDA) is widely applied by engineers to evaluate reservoirs. However, traditional analytical methods may not be accurate due to simplified assumptions, and are limited in their applications. Numerical simulation and history matching could be time and computation consuming. This research focuses on improved production data analysis and reservoir evaluation methodology. In this research, we started from a thorough study and documentation of a target field. We first reviewed the petroleum geology, petrophysical properties, and production history of the target field. We then evaluated current production histories with decline curve analysis, developed a numerical reservoir model through matching production and pressure data, and carried out parametric studies to develop an optimized waterflooding method based on ultimate oil recovery and economics. This study provides an addition to the list of carbonate fields available in the petroleum literature and also improved understandings of Smackover formation and similar analogous fields. To improve the characterization of the target field, we then developed a fit-for-purpose PDA model which is capable of evaluating reservoir properties and forecasting well performance with improved accuracy and efficiency. This model adopted an innovative Ensemble Kalman Filter (EnKF), and was couple with a single-well reservoir simulation model to evaluate reservoir properties and to predict future production. This PDA model has been validated with both synthetic simulation models and field data. It proves to be versatile, accurate, and efficient in production data analysis. The methodology helps other researchers to develop and apply more efficient production data analysis model. With the successful model development, we then carefully applied the PDA model to the analysis of production data from the target field. Permeability, skin factor, and drainage area were obtained and included in the field-scale simulation model. Parametric studies were carried out to investigate the impact of gas injection locations, the number of injectors, types of injected gas, and injection rates. Simulation strategy and workflow are summarized and has proven to be practical, accurate, and versatile to improve history matching and reservoir evaluation. Our field case studies add a reference in literature for petroleum engineers, researchers, and students to understand reservoir evaluations and field development.