Type of Document	Dissertation
Author	Wang, Feng
Author's Email Address	fwang1@lsu.edu
URN	etd-04132005-165719
Title	Long Term Pressure Behavior in Turbidite Reservoirs
Degree	Doctor of Philosophy (Ph.D.)
Department	Petroleum Engineering
Advisory Committee	Advisor Name Title Christopher D. White Committee Chair Andrew K. Wojtanowicz Committee Member Julius P. Langlinais Committee Member Zaki Bassiouni Committee Member Barb Dutrow Dean's Representative
Keywords	experimental design response surface differential depletion turbidite reservoir well testing
Date of Defense	2005-03-31
Availability	unrestricted
Abstract In this study, we investigated several possible mechanisms that would give rise to the anomalous pressure behavior (early concave-up on Horner plot or upward drift on the derivative curve of the log-log plot and asymmetry between the pressure drawdown and buildup behavior) sometimes encountered in the turbidite reservoirs in GOM primarily using numerical simulation and 2-level experimental designs. We ascertained the most influential parameters to the pressure behavior and identified that multilayer commingled system and the leaky compartment model are the most probable mechanisms to cause the anomalous behavior due to layer or zone property contrast to a certain degree. Differential depletion was found to be the main reason for the asymmetry between the pressure drawdown and buildup. Distinctive drawdown and buildup pressure behavior and numerical convolution and deconvolution were tried to obtain influence functions for discriminating the two systems. The multilayered system was further investigated quantitatively by a three-layer model representing low, medium and high properties of a reservoir using a 3-level experimental design and the response surface method. The response is the shape of the derivative curve corresponding to each combination of reservoir parameters, which is represented by the coefficients of the polynomial obtained by non-linear piecewise regression. Significant influential reservoir parameters were identified by their influence upon the shape of derivative curves when their value changed. In addition, if we have the actual pressure data obtained from well testing, we can obtain parameter value estimates by matching the derivative curve plotted from actual pressure data using the response surface models (only contains significant factors) that describe the relationship between the derivative curve shape and the factors. We may need correlate with other data source such as well logging data to verify the parameter estimates.
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