Injecting nitrogen instead of hydrocarbon gas for pressure maintenance can be an effective means to accelerate and increase the volume of hydrocarbon gas available for sale. This paper presents results of a joint study by Abu Dhabi National Oil Company (ADNOC) and ExxonMobil that used compositional full-field reservoir simulation to evaluate the suitability of N2 injection for gas cycling in a large, Middle East gas condensate reservoir. The results of the study show that substituting nitrogen for hydrocarbon gas during gas cycling has the potential to significantly accelerate the production of hydrocarbon gas for domestic gas consumption. Although late-life condensate recovery is slightly reduced, overall hydrocarbon recovery on an oil equivalent barrel (OEB) basis is improved due to higher ultimate recovery of reservoir gas. Increasing nitrogen concentrations in the produced gas stream after nitrogen breakthrough can be managed within acceptable limits by a combination of subsurface management, nitrogen removal facilities, and/or modifications to gas-consumption equipment. Various options for generating non-hydrocarbon gas for substitution were evaluated, and it was concluded that cryogenic air separation is the most cost effective method for generating large volumes of non-hydrocarbon gas within acceptable specifications. Introduction In many countries, rapid growth in power generating capacity and other industries results in substantial growth in the demand for natural gas. Increasing natural gas supplies to meet the growing demand can present a significant challenge. In areas using hydrocarbon gas injection for reservoir pressure maintenance, one option is to substitute non-hydrocarbon gas for the hydrocarbon gas injectant. Non-hydrocarbon gas substitution makes more hydrocarbon gas available for domestic use while still maintaining reservoir pressure.1 A joint study by ADNOC and ExxonMobil evaluated substituting N2 for a portion of the hydrocarbon (HC) gas injected in gas cycling operations for a large gas condensate reservoir. The study evaluated N2 injection and other alternatives to the current HC gas injection scheme. The impact of N2 substitution on recovery of HC gas, natural gas liquids (NGL), and condensate was assessed, and a conceptual facilities design sufficient for providing context to the subsurface work and progressing development planning activities was developed. As part of the study, fluid, geologic, and reservoir simulation models were updated to provide improved tools for evaluating alternative depletion plans. A number of subsurface options were evaluated to increase the amount of hydrocarbon gas available for domestic use and increase hydrocarbon recovery. Options for surface facilities were evaluated for cost, capacity, and compatibility with existing facilities. The study concluded that N2 injection is a technically feasible, low cost option and provides an economically attractive approach to increase the amount of hydrocarbon gas available for domestic Abu Dhabi consumption. Specifically the study determined the following:In a relatively short period of time, N2 substitution can make a significant portion of the hydrocarbon gas currently injected into the reservoir available for domestic consumption.N2 substitution increases overall hydrocarbon recovery (oil equivalent barrel basis) from the gas condensate reservoir.Several options are available to effectively manage the N2 content of the produced gas.N2 from air separation is the lowest cost gas substitution supply option.

Generating saturation functions (capillary pressure or J-functions), to initialize complex carbonate reservoir, always presents challenge to Petrophysicists and reservoir engineers, especially with no SCAL data available or any existing rock properties trends such as porosity-permeability relationship which are used to assign saturation function in 3D models. The proposed method requires initial water saturation (Swi) distribution in 3D model in hand (first stage) and then the Swi distribution recalculated more accurately (second stage) using group of capillary pressure (Pc) curves based on Swi intervals. Calculating Swi distribution in two stages should not impose any limitations since in the first stage Swi distribution can be estimated by many ways such as J-functions (4), group of Pc curves based on porosity intervals (part of this work). Otherwise, it may be estimated by any girding software which uses Swi log-data, but this method is not recommended since the software would give erroneous estimation of Swi in the areas of no well control such as in the transition zone area. The proposed method calculates the Swi distribution in two stages, first the Swi calculated by Pc curves based on porosity rages, then in the second stage the Swi recalculated using group of Pcs based on water saturation ranges. A script file was written to differentiate between these regions and assign saturation numbers (SATNUMs) for each saturation region which used in the simulator to initialize the dynamic model. Shuaiba reservoir is presented as study case here to demonstrate the capability of the proposed method. The proposed procedure can be to initialize huge complex carbonate reservoir such as Shuaiba formation in the United Arab Emirates. The initial water saturation profile from log data matched the water saturation calculated by the dynamic model in 90% of the wells (more than 100 wells at initial water saturation). The proposed procedure eliminates the tedious efforts to find rock property trends such as porosity-permeability correlations, which in many carbonate reservoirs may not exit, in order to assign a saturation function for each porosity/permeability range(s). The difference in initial oil in place (STOOIP) calculations between the static model (40 million cells) and the dynamic model (2.7 million cells) is less than 2 percent. It can be used also in many heterogeneous reservoirs to reduce the uncertainty in STOOIP and thus reserves estimations. Introduction: Reservoir characterization is an essential part of building robust dynamic models for proper reservoir management and making reliable predictions. Model initialization is the first critical part of 3D model building since in this part; the proper fluid saturation distribution and thus the STOOIP are calculated. The next subsequent parts (history matching and predictions) are highly dependent on model initialization. In order to calculate proper initial fluid distribution during model initialization, a good definition of reservoir rock types (RRTs) are required. The RRTs should relate somehow the geological facies to their petrophysical properties to develop proper saturation functions to initialize the model. However; this is not the case here, because there is considerable overlap of petrophysical properties in the same RRT. The RRTs in this work are mainly facies type which is lacking the petrophysical correlations and diageneces description. That is why it is a big challenge to come up with proper saturation functions to initialize the 3D model. It is difficult to differentiate between the Mercury injection capillary curves (MIPCs) for a given RRT based of porosity and/or permeability ranges. Besides, the Mercury displacing air in the MIPc measurements does not represent the correct displacement mechanism in the reservoir. The main objectives of this study are:Develop proper saturation functions (drainage capillary pressures or J-functions) using the available log data (porosity, log-Swi and log-derived permeability) to calculate the initial water saturation distribution in the 3D model and estimate proper STOOIP.Most important is to match the initial water saturation profile from logs using several wells across the field which were not affected by the injected water.

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This paper presents the implementation of an integrated reservoir modeling approach that tightly connects and integrates different reservoir modeling disciplines. The approach allows the propagation of subsurface reservoir uncertainties across the various modelling domains, from seismic interpretation though to dynamic reservoir simulation and surface facilities modeling. The results achieved by this approach is a geologically consistent ensemble of runs (100 runs or more) that matches observed data and capable of predicting the future field performance under various development scenarios with a higher degree of reliability. Using an ensemble of runs that first honor the geological facies, as initially defined in the prior probability field, and subsequently updated by reservoir production behavior in the post probability field, enables the user to predict future field performance by allowing hydrocarbon recovery probabilities to be calculated, where the impact of subsurface reservoir uncertainties on prediction results and the possible risk in each development decision is estimated. The field studied is located Offshore in Abu Dhabi and has four main, two secondary, and few minor stacked carbonate reservoirs. Available evidence indicates that the field's reservoirs are not in communication and this study focuses on the main and secondary units. The conceptual geological model proposes that all the zones are conformable, with no truncation or pinching, forming a layer cake depositional model in which reservoirs range in thickness, from few feet in thin zones, to tens of feet in thick zones. Over time the field has been affected by different tectonic stress regimes, resulting in complex strike slip faulting, extending vertically across all reservoirs. Quantification of static and dynamic uncertainties together in the applied methodology is improving the team integration and common understanding for the field structural and geomodelling uncertainties and its impact on the dynamic model behavior for different reservoirs. The methodology has been tested where new drilled well data is included at different times and it showed an easy and quick update for the entire workflow from seismic to simulation. The model was calibrated to historical observed data using different geological uncertainties (structural, facies, geomodelling and dynamic uncertainties) which helped to achieve a geologically consistent and reliable models.

The initial hydrocarbon (Oil and Gas) in-place represents the asset volume of ADNOC that is required estimation at high accuracy level with minimum uncertainties to avoid any future risks with fields' development plans. Moreover, accurate estimation of the reserves that can be produced during the field life cycle is critical as it is directly impact the CAPEX and OPEX of different field development phases.Fields developments are usually selected based on the techno-economic evaluations of the outcome from the full field simulation studies using representative models. Accordingly, management decision for fields' development is totally dependant on the accuracy of the used simulation models.Worldwide, there are many simulation models successfully demonstrating good history match profiles, nevertheless, several of these models are utilizing unsupported parameters, such as representative capillary pressure and relative permeability curves. In addition to the adverse impact on the predictive reliability, massive convergences problems that are encountered and participating in slowdown the models performance and decreasing accuracy. Subsequently, incorrect Long Term Development Plans "LTDP's" profiles will be generated. Therefore, in order to ensure achieving more representative asset volume estimates, a new procedure has been setup, established and successfully validated through different fields. The main objectives of the new procedure are to enhance model initialization with minimum gap in terms of hydrocarbon-in-place between the static and the dynamic models below the range of 1.0 %, to achieve more accuracy of the expected movable oil and gas with respect to water flooding (Current Development Plan) and future Gas/WAG flooding (LTDP), to eliminate high risk of assessment of modeling the actual gas/water breakthrough timing, recovery factor, sweep efficiency and fields measured matching parameters, and to cut down potential risks of under/over estimating the water/gas influx fronts in the reservoir.Quality match is essential in order to prevent utilization of non-measured parameters such as irreducible water saturation (Swc's), also to eliminate utilization of unproven permeability multipliers. Moreover introducing a new capillary pressures (Pc) designing concept will contribute in reducing convergences problems as well as providing more consistent dynamic model setup (dynamic model rock typing).Based on the results from several simulation studies which were introduced to the new procedure framework, the new procedure managed to demonstrate its capability to design the most reliable capillary pressure profiles. These profiles are essential for simulation models to ensure quality match of lateral and vertical oil and gas distribution in the field which represents the most extremely improvement match achieved when compared with other used method.