The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-pha...The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-phase flow. The buildup type curves or buildup behavior could be obtained through the solution by using su-perposition. But a new outer boundary condition for variable pressure boundary must be introduced to obtain the correct pressure buildup solutions by superposition. A technique is shown to determine the deviation time from the infinite-acting semilog radial flow stabilization in the derivatives of pressure, which is calculated with respect to and plotted vs. shut-in time. Field examples are given to illustrate the use of the proposed method for analyzing transient pressure data from a well located in a multi-well water-injection reservoir. An adaptive genetic algorithm-based method is used to match the pressure and pressure derivative data to estimate reservoir parameters. The validity and applicability of the proposed method are also demonstrated through the examples.展开更多
文摘The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-phase flow. The buildup type curves or buildup behavior could be obtained through the solution by using su-perposition. But a new outer boundary condition for variable pressure boundary must be introduced to obtain the correct pressure buildup solutions by superposition. A technique is shown to determine the deviation time from the infinite-acting semilog radial flow stabilization in the derivatives of pressure, which is calculated with respect to and plotted vs. shut-in time. Field examples are given to illustrate the use of the proposed method for analyzing transient pressure data from a well located in a multi-well water-injection reservoir. An adaptive genetic algorithm-based method is used to match the pressure and pressure derivative data to estimate reservoir parameters. The validity and applicability of the proposed method are also demonstrated through the examples.
