Reservoir Performance Analysis and Optimization of Gas Condensate Systems using Zero-Dimensional Reservoir Models

Open Access
Author:
Vardcharragosad, Pichit
Graduate Program:
Energy and Mineral Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
July 14, 2011
Committee Members:
  • Luis F Ayala H, Thesis Advisor
Keywords:
  • Zero-Dimensional Reservoir Model
  • Gas Condensate
  • Field Performance
Abstract:
Field performance prediction is a crucial piece of information that all relevant parties have to use in their design and decision processes during the development and exploitation of a hydrocarbon reservoir. Field performance analysis is an engineering task which requires knowledge, time, and the right tools and models. Available tools such as commercial reservoir simulators might not always be the most efficient or the most optimum solution even if they make use of highly sophisticated or detailed models. This is because these sophisticated models often require more input data and longer running time than the less detailed ones. These problems become worse when availability of input data and working time are constrained. This thesis aims to develop a field performance model which will allow engineer to perform analysis and optimization tasks more effectively for the case of gas condensate reservoirs. A gas condensate is one of the many fluid types that can be found in conventional hydrocarbon reservoirs. The development of a two-phase condition below the dew point pressure can significantly increases the complexity in engineering performance calculation. The proposed tool utilizes both zero-dimensional reservoir model customized for gas condensate and pseudo component model. Results indicate that both models can provide fairly good prediction results while requiring much less input and running time. Microsoft Excel with built-in Visual Basic for Applications (VBA) is selected as the platform to develop this simulator due to the user-friendly interface, useful built-in features, and high flexibility to use and hard-code modification. The proposed model is able to successfully predict field performance while capturing all major fluid behavior characteristics of gas condensates as well as being capable of performing various optimization tasks effectively. Limitations of the implemented pseudo component model, such as negative solution gas-oil ratios at low reservoir pressure, are elaborated and discussed. The possible sources of error and associated preventive measures derived from the use of a gas condensate tank model for the case volatile oil reservoirs are addressed. Further recommended studies on negative value of decline exponent variable and expanding current capability of the proposed model are also presented.