Summary A model was developed to predict field performance of miscible-gas injectionprojects in oilwet reservoirs. The model represents a vaporization and/orliquid extraction multiple-contact-miscible (MCM) process by astabilized-contact process by a stabilized-contact miscible process. A criticalcomponent of the model is the inclusion of a solvent relative permeability(SRP), different from the oil relative permeability, in the presence of a finaloil saturation. An example match of a misciblegas injection pilot is shown with the newmodel. Satisfactory matches of both production and injection wellperformancedata with model predictions were obtained. The pilot predictions were obtained. The pilot reservoir description was not changed to match miscible-gas floodperformance. The new model was also used performance. The new model was alsoused to match field-performance data of other pilots using the same procedure. Although not shown in this procedure. Although not shown in this paper, matchesof similar quality paper, matches of similar quality were obtained for all theother pilots. Introduction Accurate performance predictions of a miscible-gas injection project requirea reservoir simulator validated with misciblegas performance and a realisticreservoir description. Validation of a simulator that incorporates physics fora new process requires matching of actual process performance. Pilot testsprovide valuable data on the performance. Pilot tests provide valuable data onthe process performance for such validation. We process performance for suchvalidation. We conducted several miscible-gas pilots for performance data thatare the basis for the performance data that are the basis for the modeldiscussed here. This paper describes a new first contactmiscible (FCM) SRP model to predictperformance of a water-alternating-gas (WAG) performance of awater-alternating-gas (WAG) injection process in oil-wet reservoirs. Thetechnique uses a compositional model designed to operate in the modifiedblack-oil mode. An SRP (miscible gas) curve is used to approximate the mobilityof the MCM process. The SRP curve has a physical basis for vaporization- andextraction physical basis for vaporization- and extraction type MCM processesand is based on Schneider and Owens data. Wellington and Vinegar and Christiesrecently indicated that the presence of mobile water during simultaneousinjection of water and CO2 stabilizes viscous fingering compared withcontinuous CO2 injection. The new model implicitly assumes that the reservoirmixing, although significant because of dispersion, is not dominated by viscousfingering. Miscible-Gas Pilots The miscible-gas pilots, all oil-in-the-tank pilots, were normal five-spotpatterns. pilots, were normal five-spot patterns. Fig. 1 is an exampleoil-in-the-tank pilot configuration referred to as Pilot A. The pilotinjectors, Wells 21 through 26 in Fig. 1, pilot injectors, Wells 21 through 26in Fig. 1, injected the miscible gas alternately with water. The pilotproducers, Wells 19 and 20, were influenced only by the fluids injected in thepilot injectors. In general, the same statement cannot be made for invertedpatterns in which a single well injects patterns in which a single well injectsmiscible gas to surrounding producing wells. For inverted patterns, thesurrounding producers may experience the miscible-gas producers may experiencethe miscible-gas flood from the central injector and may respond simultaneouslyto a conventional oil recovery process from an area outside the pilot. In suchcases, it is much more difficult pilot. In such cases, it is much moredifficult to quantify the recovery caused solely by miscible-gas injection. The oil-in-the-tank pilots also have an advantage over loggingobservation-well pilots alone. Some of the oil-in-the-tank pilots, includingPilot A, had logging observation and fluid sampling wells to aid in theinterpretation of process performance. These wells usually are placed nearmiscible-gas injectors in a region where the reservoir pressure is above theminimum miscibility pressure is above the minimum miscibility pressure (MMP). Observation alone can pressure (MMP). Observation alone can account for neitherareal sweep nor the performance in an area where reservoir performance in anarea where reservoir pressure falls below the MMP. On the other pressure fallsbelow the MMP. On the other hand, oil-in-the-tank pilots can have areas nearthe producer where reservoir pressure may fall below the MMP. Thus, oil-inthe-tank pilots yield performance over a wide range of pressures and provide abetter data source for validating a miscible-gas simulator. Pilot Reservoir Descriptions Pilot Reservoir Descriptions The pilots weredrilled in areas of their respective fields not affected by waterflooding orwater influx. Extensive logs were obtained for all the wells, and some wellswere cored to aid in the reservoir descriptions. Waterfloods were subsequentlycompleted in each pilot to provide performance data. During this period, extensive pressure-transient data were also obtained. Initial reservoirdescriptions of the pilots were developed through geological interpretation, permeability/porosity ratio (klo) plots, and core, permeability/porosity ratio(klo) plots, and core, log, and pressure-transient data. The pilot waterfloodperformance as well as the primary and waterflood performance of the primaryand waterflood performance of the offset wells were history matched to yield afinal realistic reservoir description of each pilot. Knowledge of a realisticreservoir pilot. Knowledge of a realistic reservoir description is necessary toseparate the effects of the reservoir heterogeneities from those of themiscible-gas process variables. JPT P. 1564

Uncertainties arise while interpreting transient tests in horizontal wells. This study presents a hybrid approach in that both analytic and numeric models are used to circumvent most of the problems associated with the conventional analytic interpretation. This novel approach entails multiple steps. Initially, reservoir parameters are estimated by identifying as many flow regimes as possible using the analytic method. Thereafter, a numeric simulation model is built using a coupled wellbore-reservoir simulator. Herein, we seek to match the wellbore flow profile data, collected by production logs (PL), by adjusting local permeability and skin. This PL-matched model then allows rate calculation during the transient-test periods, using measured bottomhole pressure as the inner-boundary condition. Finally, the computed rate is convolved with pressure to interpret the drawdown data for seeking reconciliation with buildup interpretation. We present two field examples to illustrate the application of the notion presented here. Complications arise while interpreting flow and buildup tests using conventional tools, because of complex well trajectories penetrating this heterogeneous carbonate reservoir. Results show that reservoir anisotropy (kv/kh) is a very sensitive parameter and is therefore well determined. The history-matched model was quite successful in predicting the water cut behavior over 18 months in one of the wells. Introduction Interpretation of transient tests in horizontal wells is fraught with uncertainties. Complexities of long wellbore trajectory, reservoir heterogeneity, wellbore storage, variable skin along the borehole, among others, contribute to the problems associated with conventional interpretation. In fact, most test responses rarely conform to those of the idealized analytical models. Both the literature and our own experiences support this notion. Consequently, many are hesitant to collect expensive data of dubious value. Despite advancement of analytic models1–7of various formulations, interpretation of transient pressure data in horizontal wells has been a daunting task. The interpretation problem is rooted in the lack of development of various flow patterns, expected for a given geometry. Experiences suggest that often only one flow regime can be identified with certainty, thereby rendering the system indeterminate. Let us explore some of the reasons for this difficulty before offering any solution. Insights into flow dynamics in long horizontal sections perhaps hold the key to our understanding of the complex system. In-situ measurements8,9have identified some features that arise from reservoir heterogeneity and well geometry. These conditions along the well length include, among others, non-uniform reservoir pressure, variable skin, and non-uniform flux precipitated by local water sumps and gas traps in an undulating well trajectory. Frictional and accelerational pressure drops along the borehole may add another dimension to this complex problem. Occurrence of any or all of these conditions inhibits development of recognizable diagnostic features. Consequently, the use of conventional analytic methods can be limited in many cases. Indeed, gathering of a string of nonanalyzable test data may prompt some not to conduct transient tests. Therefore, questions surface, what, if anything, can be done to alleviate the problem of having to deal with data of seemingly limited value. In our proposed approach, the use of PL data is required for interpreting flow and shut-in tests. We note that the PL data have furnished the contributing borehole length in conventional test interpretation10–12using analytic models. In our approach, we match the entire wellbore influx with the coupled simulator, thereby providing a more detailed picture of reservoir heterogeneity.

A relatively large carbonate reservoir located offshore Saudi Arabia was developed over the last several years to augment production capacity. The objective was to raise the Field-A oil production capacity by an additional 25% to help offset downtime occurring on existing production platforms due to workover and facilities upgrading operations. In this paper, the development project scope, implementation, simulation, use of technology and drilling activities that resulted in a successful implementation of the development plan for the Field-A Reservoir-4, as well as the initial results, will be discussed.The development was placed on a fast implementation schedule and was carried out during a high oil demand period (2006)(2007)(2008)(2009)) that placed large constraints on delivery of new equipment and platforms. The production increment was successfully brought onstream within a 3-year timeframe. The development plan included the installation of three platforms for both oil production wells and power water injectors as well as several sidetracks to add sustainable production capacity. Key wells were equipped with permanent downhole monitoring systems to monitor reservoir pressure performance in real time and the newly drilled producers were completed with electric submersible pump (ESP) lift systems. In addition, the first application in Saudi Aramco of a distributed temperature sensor (DTS) system was deployed in an injector to obtain real time flow profiles along the wellbore section.The overall development project utilized a number of existing assets to minimize the development cost and trial testing of the innovative applications, such as using existing wells for on-platform water injection that consists of a water supply and an injection well combination while both located on the same platform, and an inverted ESP assisted water injection.

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