TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractOne of the classic problems in the development of a reservoir numerical simulation model is the question of scale. Data that are acquired from many different sources give us a view of the reservoir under different constraints. In this paper, we present a technique that integrates data from the core scale to that acquired through logs to well-test pressure transient analysis (PTA) and, finally, to the production history information. A field example from the Neuquen Basin demonstrates this procedure.PTA offers a reasonable estimate of the permeability within the drainage radius of the well.Unfortunately, these measurements usually are not made in every well. Log data typically is acquired in the field from most wells. Using recovered core data and permeability analysis from cores, a probabilistic petrophysical model, honoring that core data, is constructed. The petrophysical model is applied throughout the field and used in constructing a geocellular model. The model can be investigated in positions equivalent to the volumes investigated by the PTA, and the petrophysicallyderived permeability can be iteratively modified to match the permeability derived from the PTA. The geocellular model is upscaled for dynamic fluid-flow simulation. Finally, the production history is compared with the simulation results. The process becomes an iterative loop to achieve the best match of all the available data. This process facilitates the final history match to gas, oil and water production.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe Chihuido de la Salina field is situated in the folded thrust belt of the Neuquen basin of Argentina. The field is composed of several structural blocks, which have gas caps of different relative sizes. The most important blocks have oil legs in steeply dipping flanks. The structure presents particular problems for both geologic modeling and numerical simulation for the generation of a waterflood development plan. This paper presents the techniques used to incorporate pertinent information from many different disciplines and create a numerical model that enables reasonable predictions for a variety of development scenarios.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractOne of the classic problems in the development of a reservoir numerical simulation model is the question of scale. Data that are acquired from many different sources give us a view of the reservoir under different constraints. In this paper, we present a technique that integrates data from the core scale to that acquired through logs to well-test pressure transient analysis (PTA) and, finally, to the production history information. A field example from the Neuquen Basin demonstrates this procedure.PTA offers a reasonable estimate of the permeability within the drainage radius of the well.Unfortunately, these measurements usually are not made in every well. Log data typically is acquired in the field from most wells. Using recovered core data and permeability analysis from cores, a probabilistic petrophysical model, honoring that core data, is constructed. The petrophysical model is applied throughout the field and used in constructing a geocellular model. The model can be investigated in positions equivalent to the volumes investigated by the PTA, and the petrophysicallyderived permeability can be iteratively modified to match the permeability derived from the PTA. The geocellular model is upscaled for dynamic fluid-flow simulation. Finally, the production history is compared with the simulation results. The process becomes an iterative loop to achieve the best match of all the available data. This process facilitates the final history match to gas, oil and water production.
Recent advances in development of hardware for reservoir monitoring have caused rapid changes in production logging and testing techniques for instrumented wells. On-demand actuations of downhole valves and data acquisition from the downhole gauges remain available well into the useful well life due to improved reliability of the downhole equipment. A specific layout of the gauges could be tailored to support various types of production logging, and pressure transient and production tests1,2. Instead of the often costly one-off surveys required for a the non-instrumented wells, both data gathering and interpretation become part of a continuous surveillance cycle for an instrumented, "intelligent" well. The resulting exhaustively sampled data sets from instrumented wells are typically very large and require substantial cleansing and cross-calibration with a range of physical models as well as empirical trends to extract valuable information encoded in the data3. Most of these workflows also support decision making in real time. The paper outlines practical ways of combining known well-testing principals with the modern downhole completion instrumentation to estimate production rate, productivity index, and reservoir pressure using surveillance workflows for a multi-zone intelligent completion in the Korchagina field, Russia. Data from permanent downhole pressure gauges supports a number of real-time workflows including those for zonal rate and productivity allocation. Sequential valve cycling can be interpreted as a multi rate inflow test and, when combined with initial well test data, can calibrate the rate allocation procedure. Meeting production goals for each of the zones requires a real-time optimization technique for setting the valve positions. The procedure was implemented in a form of automated surveillance software for pressure, rate, and productivity allocation and does not require shut-ins to obtain well test data.
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