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Abstract

One important goal in reservoir testing is to determine the reservoir characteristics and the well's productivity. Measurements which can contribute to this goal include well logging, fluid sampling, pressure transient testing, and production profiling. A careful analysis of these measured production profiling. A careful analysis of these measured data will provide adequate information for well evaluation. The purpose of this paper is to show how an integrated reservoir purpose of this paper is to show how an integrated reservoir testing methodology in conjunction with a human engineered procedure on computer enhances the reservoir characterization procedure on computer enhances the reservoir characterization and the evaluation of well performance.

This integrated methodology includes concepts, which have been implemented in recent approaches to reservoir testing and NODAL* analysis. During the design phase of each test, sensitivity studies provide insights that facilitate adequate data gathering for valid interpretation, which can help minimize the cost of the test. During interpretation, the central issue is to identify a realistic reservoir model which reflects the transient pressure and rate behavior. Here significant use is made of the log-log plot of pressure change and its derivative with respect to superposition time. Systematic diagnosis of the log-log plot helps identify different flow regimes, while specialized plots and type curve analysis provide a basis for the estimation of reservoir parameters. Lastly, the computed results can be easily integrated into a NODAL analysis to study and evaluate the well's productivity.

The examples presented illustrate the benefits of a systematic approach to reservoir test design and interpretation, and well productivity evaluation. The computer procedure also has the advantage of incorporating input data from several sources, including openhole logs and the Repeat Formation Tester (RFT*) tool.

Introduction

During well testing operations, pressure, flow-rate and temperature transients are generally recorded using testing devices and the Production Logging tools (PLT). With the tools in a stationary position in the wellbore, the transient behavior of the reservoir is observed by varying the surface flow-rates. On the other hand, under stabilized and shut-in conditions, production logging measurements are conducted versus depth. Interpretation of these different types of data help the engineer to quantify the well/reservoir model, and to diagnose well performance.

The methodology outlined in this paper integrates a test design approach, currently acceptable acquisition procedures, interpretation techniques and NODAL analysis. procedures, interpretation techniques and NODAL analysis. For both vertical and horizontal wells, the interpretation procedures include the log-log presentation, the use of procedures include the log-log presentation, the use of pressure derivative for identifying dominant flow regimes, pressure derivative for identifying dominant flow regimes, convolution type curves and the convolution derivative when downhole flow-rates are available, and an automatic parameter estimation. Lastly, the integrated reservoir parameter estimation. Lastly, the integrated reservoir engineered methodology shows how interpreted results can be easily utilized to evaluate the performance of a well via NODAL analysis./

Several examples are presented to illustrate how the integrated methodology of test design, data acquisition, interpretation and well evaluation was encapsulated into a human engineered computer environment. The first example illustrates the advantage of downhole shut-in during a buildup test. The second example illustrates how different aspects of the interpretation procedure aid in evaluating late time effects. The next example demonstrates the transient response of a horizontal well test, the flow regimes that occured and the analysis thereof. Lastly, the evaluation of the horizontal well performance is compared with that of a vertical well using the NODAL analysis.

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