Semester

Summer

Date of Graduation

2007

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Petroleum and Natural Gas Engineering

Committee Chair

Shahab Mohaghegh.

Abstract

The process of continuously monitoring and analyzing data in real time as well as reacting to events in an effective and more efficient manner represents one of the challenges in the oil and gas industry today. The existence of a computer model that is capable of evaluating data that enters a computer database in real time, performs different kinds of production analysis, and predicts reservoir performance opens new possibilities for field optimization. Having a model that alerts the engineers of abnormal situations during production operations will help to decrease the time of reaction to such events and as a result will optimize the processes.;The first building blocks for Smart Field Data Analysis that will serve as the bridge for building a more complex computer model to evaluate the data as it is being measured from the production fields; forecast production behavior and report unexpected situations from the measurements has been be the goal of this study.;A computer program (Smart Field Data Analysis-SFDA 1.0) capable of reading high frequency data and presenting it in real time has been created. One of the main problems encountered during this process was dealing with high frequency data. A process that summarizes this type of data while preserving its integrity has been developed. After the high frequency data has been summarized different types of production analysis have been performed using actual real time data generated from a storage field provided by Columbia Gas Transmission Corporation. Material balance analysis has been carried out in order to estimate gas in place and determine whether a leak is presented in the reservoir. Decline Curve Analysis has also been included to forecast gas production. In addition, the program is capable of detecting pressure transient periods in which the high frequency data containing such information will be stored and accessible for well testing analysis. Finally, real time data using Eclipse Simulator has been generated and tested during different scenarios to validate the work previously done.

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