Pressure Transient Formation and Well Testing

Convolution, Deconvolution and Nonlinear Estimation

Nonfiction, Science & Nature, Technology, Petroleum, Business & Finance, Industries & Professions, Industries
Cover of the book Pressure Transient Formation and Well Testing by Fikri J. Kuchuk, Mustafa Onur, Florian Hollaender, Elsevier Science
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Author: Fikri J. Kuchuk, Mustafa Onur, Florian Hollaender ISBN: 9780080931746
Publisher: Elsevier Science Publication: August 4, 2010
Imprint: Elsevier Science Language: English
Author: Fikri J. Kuchuk, Mustafa Onur, Florian Hollaender
ISBN: 9780080931746
Publisher: Elsevier Science
Publication: August 4, 2010
Imprint: Elsevier Science
Language: English

This reference presents a comprehensive description of flow through porous media and solutions to pressure diffusion problems in homogenous, layered, and heterogeneous reservoirs. It covers the fundamentals of interpretation techniques for formation tester pressure gradients, and pretests, multiprobe and packer pressure transient tests, including derivative, convolution, and pressure-rate and pressure-pressure deconvolution. Emphasis is placed on the maximum likelihood method that enables one to estimate error variances in pressure data along with the unknown formation parameters.

  • Serves as a training manual for geologists, petrophysicists, and reservoir engineers on formation and pressure transient testing
  • Offers interpretation techniques for immediate application in the field
  • Provides detailed coverage of pretests, multiprobe and packer pressure transient tests, including derivative, convolution, and pressure-rate and pressure-pressure deconvolution
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This reference presents a comprehensive description of flow through porous media and solutions to pressure diffusion problems in homogenous, layered, and heterogeneous reservoirs. It covers the fundamentals of interpretation techniques for formation tester pressure gradients, and pretests, multiprobe and packer pressure transient tests, including derivative, convolution, and pressure-rate and pressure-pressure deconvolution. Emphasis is placed on the maximum likelihood method that enables one to estimate error variances in pressure data along with the unknown formation parameters.

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