Reservoir Characterization Constrained to Well Test Data: A Field Example (1996)

Reservoir Characterization Constrained to Well Test Data: A Field Example J.L. Landa, SPE, Stanford University, M.M. Kamal, SPE, and C.D. Jenkins, SPE, ARCO Exploration and Production Technology, and R.N. Horne, SPE, Stanford University Abstract This paper presents a method to integrate well test, production, shut-in pressure, log, core, and geological data to obtain a reservoir description for the Pagerungan Field, offshore Indonesia. The method computes spatial distributions of permeability and porosity and generates a pressure response for comparison to field data. This technique produced a good match with well test data from three wells and seven shut-in pressures. The permeability and porosity distributions also provide a reasonable explanation of the observed effects of a nearby aquifer on individual wells. As a final step, the method is compared to an alternate technique (object modelling) that models the reservoir as a two-dimensional channel. Introduction The Pagerungan field has been under commercial production since 1994. This field was chosen to test a method of integrating dynamic well data and reservoir description data because:the reservoir has only produced single phase gas,one zone in the reservoir is responsible for most of the production, andgood quality well test, core, and log data are available for most wells. The method that was used to perform the inversion of the spatial distribution of permeability and porosity uses a parameter estimation technique that calculates the gradients of the calculated reservoir pressure response with respect to the permeability and porosity in each of the cells of a reservoir simulation grid. The method is a derivative of the GPST approach described in Appendices A and B. The objective is to find sets of distributions of permeability and porosity such that the calculated response of the reservoir closely matches the pressure measurements. In addition, the sets of permeability and porosity must satisfy certain constraints given by the geological model and by other information known about the reservoir. Statement of Theory and Definitions The process of obtaining a reservoir description involves using a great amount of data from different sources. It is generally agreed that a reservoir description will be more complete and reliable when it is the outcome of a process that can use the maximum possible number of data from different sources. This is usually referred to in the literature as "Data Integration". Reservoir data can be classified as "static" or "dynamic" depending on their connection to the movement or flow of fluids in the reservoir. Data that has originated from geology, logs, core analysis, seismic and geostatistics can be generally classified as static; whereas the information originating from well testing and the production performance of the reservoir can be classified as dynamic. So far, most of the success in data integration has been obtained with static information. Remarkably, it has not yet become common to completely or systematically integrate dynamic data with static data. A number of researchers are studying this problem at present. This work represents one step in that direction. Well Testing as a Tool for Reservoir Description Traditional well test analysis provides good insight into the average properties of the reservoir in the vicinity of a well. Well testing can also identify the major features of relatively simple reservoirs, such as faults, fractures, double porosity, channels, pinch-outs, etc. in the near well area. The difficulties with this approach begin when it is necessary to use the well test data on a larger scale, such as in the context of obtaining a reservoir description. P. 177