Analysis of Relatively Short Variable Rate “Noisy” Well Test Data Using Non-Linear Deconvolution

Öz

Short well test data are pressure-rate-time data that are not long enough to be used to infer the reservoir boundary model and are very common in the oil and gas industry. Short rate well test data may occur when companies try to cut costs of well test jobs or mostly due to improper well test design. Nevertheless, one may wish to extract the most amount of information from this limited data because the de-convolve response can allow the reservoir engineer to make the best use of the available data in selecting a suitable interpretation model by narrowing down the possible boundary models and also providing a reliable estimates of model parameters. The aim of this study is to demonstrate the usefulness and significance of pressure-rate deconvolution in analyzing relatively short variable rate data using a hypothetical case study. The simulation was carried out using Sapphire’s test design module by assuming the presence of an exploratory well in an oil reservoir above bubble point pressure. Further assumption is that the reservoir is homogenous, therefore the possibility of a changing wellbore model was neglected from the analysis. The computer codes for the simulation were inputted using python programming language. We observed from the study that although pressure and flow rate relationship can be nonlinear, the problem can be formulated as a linear problem and the nonlinearity is expressed in the features of the reservoir. The simulation results were satisfactory using the test case and deviations between model parameters and actual reservoir parameters used in simulation was shown to have an absolute value less than 8% which is within acceptable engineering limits.

Anahtar Kelimeler

• Pressure transient
• Reservoir boundaries
• Semi-infinite
• Sapphire
• Pressure build-up

Kaynakça

1. [1] S. Chapra, R. Canale, Numerical methods for engineers, 6th ed., Boston: McGraw-Hill, 2006, pp 78 – 104.
2. [2] L. Dake, Practice of Reservoir Engineering, 1st ed., Amsterdam: Elsevier Science, 1994, pp 147-154.
3. [3] A. Gringarten, “From Straight Lines to Deconvolution: The Evolution of the State of the Art in Well Test Analysis” SPE Reservoir Evaluation & Engineering Journal, vol. 11, pp 41-62, 2008.
4. [4] O. Houze, E. Tauzin, O. Allain, “New Methods to deconvolve Well-Test Data under Changing Well Conditions”, SPE Annual Technical Conference and Exhibition, Florence, pp. 20-22 September 2010.
5. [5] F. Kuchuk, M. Onur, F. Hollaender, Pressure transient formation and well testing, 11th ed., Amsterdam: Elsevier, 2010, pp 76 – 77.
6. [6] M. Levitan, “Practical Application of Pressure-Rate Deconvolution to Analysis of Real Well Tests”, SPE Reservoir Evaluation & Engineering Journal, vol. 8, pp 113-121, 2005.
7. [7] M. Levitan, G. Crawford, A. Hardwick, “Practical Considerations for Pressure-Rate Deconvolution of Well Test Data”, SPE Reservoir Evaluation & Engineering Journal, vol. 11, pp 35-47, 2006.
8. [8] T. Von Schroeter, F. Hollaender, A. Gringarten, “Deconvolution of Well Test Data as a Nonlinear Total Least Squares Problem”, SPE Annual Technical Conference and Exhibition, New Orleans, p 30 September – 3 October 2001.

9. [9] T. Von Schroeter, F. Hollaender, A. Gringarten, “Deconvolution of Well Test Data as a Nonlinear Total Least Squares Problem”, SPE Reservoir Evaluation