A New Technique for Determining Reservoir Description from Field Performance Data
- K.H. Coats (The U. of Texas) | J.R. Dempsey (The U. of Texas) | J.H. Henderson (International Computer Applications Ltd.)
- Document ID
- Society of Petroleum Engineers
- Society of Petroleum Engineers Journal
- Publication Date
- March 1970
- Document Type
- Journal Paper
- 66 - 74
- 1970. Society of Petroleum Engineers
- 5.3.2 Multiphase Flow, 5.5.8 History Matching, 5.1.2 Faults and Fracture Characterisation, 4.6 Natural Gas, 5.5 Reservoir Simulation, 5.1 Reservoir Characterisation
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Reservoir description data largely determine the validity of simulated reservoir performance. This paper presents a method that employs the least paper presents a method that employs the least squares and linear programming techniques to determine a reservoir description from given performance data. The method bandies multiphase performance data. The method bandies multiphase as well as single-phase flow Problems.
The description parameters determined by the method may be any physical properties that influence calculated field performance. We believe The technique offers considerably greater efficiency than previously reported techniques.
Example applications presented include cases of single-phase gas flow, single-phase oil flow and two-phase gas-water flow. In these particular applications the method gave accurate results with a large range of uncertainty in the reservoir parameters, and with a small number of simulation parameters, and with a small number of simulation runs.
The purpose of reservoir simulation is estimation of future reservoir performance under alternative well configurations or operating conditions. This estimation is increasingly being performed using rather complex, numerical reservoir models. Reservoir description data constitute the bulk of the required input data for these models, and the accuracy of these data largely determine the validity of the calculated results. Thus an obvious problem is the determination of an accurate problem is the determination of an accurate reservoir description.
We treat the problem of determining a reservoir description that, when used as input data to a reservoir simulator, results in close agreement between calculated and observed field performance. Field history or performance data are presumed available for some period of time designated the "match period". The available field history may reflect single- or multiphase, multidimensional flow, and the performance data to be matched may be any mix of observed pressures, producing rates, gas-oil and/or water-oil producing ratios. The observed field performance may correspond to a period of depletion and/or injection, or to an period of depletion and/or injection, or to an interference test.
Our method for determining a viable reservoir description requires a number of runs using a reservoir simulator, each run using a reservoir description that is random within limits specified by the engineer. We then use a second, small program, that utilizes least squares and linear program, that utilizes least squares and linear programming; techniques, to process the data output programming; techniques, to process the data output from those runs to determine a reservoir description.
To illustrate and test this new method, we constructed three example reservoirs experiencing single-phase gas, single-phase oil and two-phase (gas-water) flow, respectively, in two spatial dimensions. Simulator runs were made using a given set of reservoir description parameters. The results of these runs were then treated as "data" and the description parameters considered unknown. The automatic history matching method described in this paper was applied to back out description parameter values from the performance "data". parameter values from the performance "data". The agreement between these values and the true parameter values is given below. parameter values is given below. Reed et al. present an actual field case where the manual approach to matching production history proved prohibitive in both man and machine time. proved prohibitive in both man and machine time. Our least squares, linear programming technique was then used to achieve a satisfactory and economical match of the reservoir performance data.
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