AN INITIAL GUESS FOR THE LEVENBERG-MARQUARDT ALGORITHM FOR CONDITIONING A STOCHASTIC CHANNEL TO PRESSURE DATA
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dc.contributor.author | Zhang F. | |
dc.contributor.author | Reynolds A.C. | |
dc.contributor.author | Oliver D.S. | |
dc.date.accessioned | 2022-01-25T05:52:44Z | |
dc.date.available | 2022-01-25T05:52:44Z | |
dc.date.issued | 2003 | |
dc.identifier | https://elibrary.ru/item.asp?id=4993161 | |
dc.identifier.citation | Mathematical Geology, 2003, 35, 1, 67-88 | |
dc.identifier.issn | 0882-8121 | |
dc.identifier.uri | https://repository.geologyscience.ru/handle/123456789/34592 | |
dc.description.abstract | A standard procedure for conditioning a stochastic channel to well-test pressure data requires the minimization of an objective function. The Levenberg-Marquardt algorithm is a natural choice for minimization, but may suffer from slow convergence or converge to a local minimum which gives an unacceptable match of observed pressure data if a poor initial guess is used. In this work, we present a procedure to generate a good initial guess when the Levenberg-Marquardt algorithm is used to condition a stochastic channel to pressure data and well observations of channel facies, channel thickness, and channel top depth. This technique yields improved computational efficiency when the Levenberg-Marquardt method is used as the optimization procedure for generating realizations of the model by the randomized maximum likelihood method. | |
dc.subject | STOCHASTIC SIMULATION | |
dc.subject | MATCHING PRESSURE DATA | |
dc.subject | OPTIMIZATION | |
dc.subject | RANDOMIZED MAXIMUM LIKELIHOOD METHOD | |
dc.subject | MODELING CHANNELS | |
dc.title | AN INITIAL GUESS FOR THE LEVENBERG-MARQUARDT ALGORITHM FOR CONDITIONING A STOCHASTIC CHANNEL TO PRESSURE DATA | |
dc.type | Статья |
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