SPE/EAGE Reservoir Characterization & Simulation Conference

Giant reservoirs of the Middle East are crucial for the supply of oil and gas to the world market. Proper simulation
of these giant reservoirs with long history and large amount of static and dynamic data requires efficient parallel
simulation technologies, powerful visualization and data processing capabilities.
This paper describes GigaPOWERS, a new parallel reservoir simulator capable of simulating hundreds of millions
of cells to a billion cells with long production history in practical times. The new simulator uses unstructured grids.
A distributed unstructured grid infrastructure has been developed for models using unstructured or complex
structured grids. Unconventional wells such as maximum reservoir contact wells and fish-bone wells, as well as
faults and fractures are handled by the new gridding system. A new parallel linear solver has been developed to
solve the resulting linear system of equations. Load balancing issues are also discussed.
A unified compositional formulation has been implemented. The simulator is designed to handle n-porosity
systems. An optimization-based well management system has been developed by using mixed integer nonlinear
programming. In addition to the core computational algorithms, the paper will present the pre- and postprocessing
software system to handle large amount of data. Visualization techniques for billions of cells are also
presented

The purpose of the simulation history match phase in a study is to achieve a simulation model calibrated to historical performance for predictive production forecasting while preserving reservoir understanding in terms of reservoir characterization and fluid flow mechanisms. The classical history match simulation approach involves running a number of history match simulation cases with modified simulation model variables to obtain only one of the many probable match models to the field data. Undoubtedly, the conventional simulation history match approach does not normally handle the uncertainty of all model variables, nor the possibility to identify and carry forward a set of multiple equi-probable history match model scenarios to predictive forecasting. Furthermore, the conventional history match approach lacks a rigorous mechanism to ensure that the original reservoir characterization and understanding is preserved after achieving only one of the many probable history match models. This paper presents an innovative history match approach as part of Saudi Aramco’s integrated “Event Solution1” study workflow. This approach was developed to enable faster simulation history match under uncertainty, in terms of static and dynamic variables. The history matching process is performed with the aid of assisted history matching software 2 that tracks the match quality of hundreds of history match cases and analyzes the impact of each variable and its range of uncertainty on model match quality to historical field data. Finally, a proxy (statistical History Match solution surface including all uncertainty variables) is created that combines model learnings to provide directional guidance to a most likely history match model design. As the history match process progresses, history match variables are characterized into three distinct categories; (1) critical variables to history match, (2) non critical variables to history match but with significant impact on prediction, and (3) non critical variables to history match but with less impact on prediction. The impact of the variables on prediction is concluded by concurrently running prediction runs under uncertainty. The uncertainty range of the variables categorized in groups (1) and (3) are set to a single realizations or narrower range of uncertainty for each variable while group (2) variables are carried forward with a more restricted range of uncertainty (defined by history match quality analysis) setting the stage for prediction under uncertainty modeling. This paper presents the application of an innovative history match approach that provides all project stakeholders with a shared understanding of critical and non critical uncertainties (static and dynamic) in history match as carried forward to prediction runs under uncertainty.

Asphaltene and wax depositions in the course of production of many Iranian reservoirs have become a serious problem. In order to investigate the effects of injecting rich and dry gases and also nitrogen, on the asphaltene precipitation process, a comprehensive research study was launched. The three phase equilibrium calculation of NGHIEM and his colleagues was used [6]. In the method pure asphaltene in the oil was considered as solid and the heavy part of the oil was split as precipitating and nonprecipitating.
The provided model was able to describe the phase behavior of reservoir oil encountered with a compositional disturbance caused by injecting light fluids into the reservoir during the production period. In this work, first, the natural depletion model of each case was constructed and then the changes of behavior by injecting rich and dry natural gases and also high nitrogen content gas were investigated. Also the changes in the onset of asphaltene precipitation for different injections were shown. The achieved results showed that the nitrogen gas had more moderate effect on precipitation process compared to more vigorous effect of dry and rich gases.

This paper presents an application of integrated asset modeling to a giant offshore oil field. The field is located northwest of Abu Dhabi Island and is one of the largest offshore fields in the world. The asset comprises several individually modeled reservoir layers sharing a common surface facility. The traditional method of modeling this field involves running separate simulation models assuming fixed boundary conditions at the wellhead. This does not accurately model the effects of the constraints imposed by the surface facility. The primary aim of this paper is to highlight the importance of integrated asset modeling in formulating an optimized, cost- effective development plan. This is achieved through the provision of realistic production profiles, taking into account the impact of system backpressure and changes in operating conditions. Secondly, integrated modeling acts to reduce uncertainty in the design data in terms of phased production for future facility upgrading and replacement. Finally, integrated modeling provides a framework for production system optimization under different development schemes. Included in the discussions presented here are a validation of the integrated asset modeling tool, an overview of the business requirements for the operation of the field over the next 30 years, and analysis of selected development strategies highlighting the added value of integrated asset modeling. The results of the integrated studies helped to formulate decisions on infill drilling based on realistic production profiles. Secondly, they served to reduce risk through better understanding of the surface and subsurface interaction. Thirdly, they helped to support the decision for commissioning a new concept facility layout (artificial islands), which represents a significantly lower CAPEX investment with more flexibility. Finally, the integrated study assisted in making decisions on the application and type of artificial lift and displacement mechanisms.

The Inflow Performance Relationship (IPR) describes the behavior of the well’s flowing pressure and production rate, which is an important tool in understanding the reservoir/well behavior and quantifying the production rate. The IPR is often required for designing well completion, optimizing well production, nodal analysis calculations, and designing artificial lift. Different IPR correlations exist today in the petroleum industry with the most commonly used models are that of Vogel’s and Fetkovitch’s. In addition to few analytical correlations, that usually suffers from limited applicability. In this work, a new model to predict the IPR curve was developed, using a new correlation that accurately describes the behavior the oil mobility as a function of the average reservoir pressure. This new correlation was obtained using 47 actual field cases in addition to several simulated tests. After the development of the new model, its validity was tested by comparing its accuracy with that of the most common IPR models such as Vogel, Fetkovitch, Wiggins, and Sukarno models. Twelve field cases were used for this comparison. The results of this comparison showed that: the new developed model gave the best accuracy with an average absolute error of 6.6 %, while the other common models are ranked, according to their accuracy in the following order to be Fetkovich, Sukarno, Vogel, and Wiggins, with average absolute errors of 7 %, 12.1 %, 13.7 %, and 15.7 respectively. The new developed IPR model is simple in application, covers wide range of reservoir parameters, and requires only one test point. Therefore, it provides a considerable advantage compared to the multipoint test method of Fetkovich. Moreover, due to its acuuracy and simplicity, the new IPR provides a considerable advantage compared to the widely used method of Vogel.

Mercury injection capillary pressure data have been widely used to charaterize reservoir rocks, evaluating sealing capacity for traps and to explain the locations of hydrocarbon accumulations and transition zones. This method can determine a broader pore size distribution more quickly and accurately than other methods. It can be used to characterize pores ranging from 0.003 pm to 360 μm using a single theoretical model. The data produced (mercury intrusion volume at various pressures) can be used to calculate numerous sample characteristics such as pore size distributions, total pore volume, total pore surface area, median pore diameter, and sample densities (bulk and skeletal). In this study the application of the high pressure mercury porosimetry technique in determination of different reservoir parameters have been investigated and a comparison between clastic and non clastic reservoirs was made. This was done by using data obtained from forty core samples from sandstone and carbonate reservoirs in North Africa. The results of different measurements and techniques were processed and interpreted. Theses included calculating the capillary pressure curves for the two rock types, converting the air/mercury curves to subsurface conditions and making sensitivity analysis for different parameters such as interfacial tension and contact angle. The distribution of pore-throat sizes and thus understanding the structures of pore systems in the reservoir has also been investigated. Another petrophysical reservoir property which was examined by this method was the existence of different types of porosity, (micro, meso and macro), which can be derived from the pore size distributions and compared between the two rock types, and therefore an attempt was made to classify the
different rock types present in the studied samples. A set of Empirical relationships which relate absolute permeability to the pore throat size distribution, pore throats at different mercury saturations, were derived for each rock type, and then these relationships were more investigated by introducing the effect of porosity. Finally, an estimation of the pore size from routine core data was made and compared with the measured data. These empirical relationships were also compared with other available relatioships obtained by other authors such as Pittman and Winland.

Multiple contact miscibility test for both forward and backward technique was conducted on light live reservoir crude with the API value of 41.5o. The experiment was conducted in four stages. At each stage of the experiment, a small amount of liquid and gas were sampled out from the PVT cell for compositional analysis.The multiple contact miscibility test simulate the continuous multiple contact process when the injection gas Carbon Dioxide (CO2) is injected into the reservoir fluid. In this study, the injection gas was mixed with the crude oil to achieve equilibrium at reservoir pressure and temperature. Dynamic miscibility between oil and Carbon Dioxide, which was not miscible on first contact was achieved by in-situ mass transfer of components between phases. This mass transfer phenomena, however, is not the same for forward and backward method of multiple contact miscibility test. At each stages of the test, different component has been transferred between phases with different amount and rate. The results indicate that the amount of methane in vapour phase had increased significantly, as the number of contacts increases for both forward and backward multiple contact tests. The intermediate fraction became lighter and lighter as the contact progress. While the heavier component that was left out in the liquid phase susceptible to flocculate and produce heavy deposit such as asphaltenes. The phase envelope for liquid phase was generated using PVTi software with compositional data as an input. The change in the phase envelope shape explained the process that happened at each stages of the experiment. Ternary diagram was build to explain the difference in extraction process between forward and backward multiple contact test. In conclusion, for CO2, some period of immiscible displacement must occur before mass transfer between reservoir oil and the advancing gas front establishes dynamic miscibility. This phenomenon was observed for both backward and forwards multiple contact experiment.

The characterization of the unconventional reservoirs is a challenge. Though the Jurassic formation, Najmah-Sargelu, in North Kuwait fields have been tested and found to be a prolific source-rock as well as a producer of gas, condensate and volatile oil in several wells, but raised the flagged issue as regards to its characterization and predictability for success. The drill stem test (DST) results at some wells are quite successful without any stimulation, while at other wells the DSTs are unsuccessful in spite of advanced and repeated stimulations. Thus resulting a success rate at 50% and categorizing the Najmah-Sargelu as a geologically-complex, naturally-fractured, tight gas and condensate reservoir. The Najmah kerogen member, formally known as Najmah shale, the source-reservoir composed of highly organic rich argillaceous and calcareous clay, represented by very high total gamma ray values associated with high uranium on spectral gamma logs. The Sargelu limestone, underlying the Najmah kerogen and overlying Dhruma shale, is generally tight and occasionally fractured. Conventional characterization by multi disciplinary data integration and model could not explain the test results, suggesting the key factor making these kerogen reservoirs to producer lies outside our scanned parameters such as structural position, fractures and formation damage etcetera. Conventional petrophysical interpretation and integrated formation evaluation method fell short to explain the unique behavior of such reservoirs. This paper illustrates the new parameter, organic richness of Najmah kerogen sub-units and the pattern relationship between the success as flowed and unsuccessful as no-flow DSTs from the well data. Thus characterizing the Najmah reservoir based on their organic richness, derived from wireline density logs. This approach has successfully predicted our recent Najmah completed wells. Understanding this critical factor will navigate the 3D model building workflow steps for seismic reservoir description and future development strategy of Najmah in north Kuwait and other regions as well.

The Umm Gudair is a large matured carbonate reservoir of Kuwait with a production history of more than 45 years. Umm Gudair has been producing primarily from the Lower Cretaceous Minagish Oolite formation composed of porous limestone consisting primarily skeletal grainstones. In recent past, the main focus of the asset team on this reservoir has been to extend the plateau rate and devise a long term Field development Plan by developing a comprehensive 3D geocellular model which shall be used for running simulation. Three cases of 3D structural modeling scenarios were considered in order to reduce uncertainty attributed to velocity models. Petrophysical data of 223 wells, Core data from 34 wells, 3D Seismic Cube along with Inversion derived porosity and High Pressure Mercury Injection (Capillary Pressure) data from 102 core-plugs were used to generate 3D property model with the help of advanced 3D geomodeling software. A Facies classification model was built utilizing observations from core description, Log data and training a supervised neural network. Porosity was modeled using sequential Gaussian simulation (SGS) honoring core observations and Seismic derived porosity cube. Modeling Permeability was most critical and complex. Analysis of core data suggested a wide variation in Permeability (between 0.2 to 4000mD) with corresponding porosity variation of 0.08 to 0.30. Average capillary pressure data from core observations was converted to Height Vs Initial Water Saturation (J-Function) and water saturation was modeled. Despite the abundance of Log, Core, Seismic and laboratory data, creating a truly representative 3D Geomodel was a big challenge owing to complex relationship and distribution amongst various petrophysical properties. This
paper highlights the integration of various data and comprehensive steps of building a consistent representative 3D geocellular model used for flow simulation studies and field development planning.