bluuebunny/crossref_metadata_2025_split huggingface dataset:
SubFace Matrix-Fracture Transfer Function: Improved Model of Gravity Drainage/ Imbibition
Authors: Abushaikha Ahmad S. A. , Gosselin Olivier R. 
Published: June 2009

Abstract
Gravity is a major recovery mechanism of naturally fractured reservoirs, where fracture gas drains matrix oil until equilibrium is reached with the capillary forces (wrt fluid densities, matrix gas capillary pressure and block height). The challenge of modelling gravity drainage in dual-medium simulation is to match the final maximum recovery, using integrated pseudo-capillary pressure curve, and the correct recovery kinetics. The paper suggests an approach to improve the simulation of the recovery kinetics in gravity drainage by dividing the matrix block for the fluid transfer function in two specific parts: saturation front part (SFP) and initial state part (ISP). As the invading gas enters the matrix the SFP and ISP areas increase and decrease respectively, until the final recovery is reached at equilibrium point. The contributions from each part are summed up to equal a mass conservation equation at each time step for each matrix cell. Properties of SFP depend on the invading fluid saturation and ISP hold the initial state properties, hence its name. This SubFace formulation can be implemented in flow simulator for reservoirs exhibiting a dual-medium behaviour.
Our SubFace Transfer Function approach (SF), performs well versus not only conventional transfer functions (Kazemi, Gilman), but also versus two improved ones: Quandalle-Sabathier, and Lu-Blunt (non-Warren-Root General Transfer Function) in matching the results of fine-grid single-medium models under various parameters (capillary pressure, matrix shape and mobility). We also tested SF in mixed-wet water-oil system to assess its capability of modelling gravity and capillary imbibition.
This new formulation improves dual-medium simulations of fractured reservoirs with an accurate representation of matrix-fracture exchanges, and better reserves assessment and reservoir management.
Reservoir Facies Modeling Using Intelligent Data Gathering in an Iranian Carbonate Field
Authors: Lakzaie A. , Ghasem-Alaskari M. K. , Vaziri S. M. 
Published: June 2009

Abstract
The construction of facies model is one of the most crucial undergone procedures of any stochastic geomodeling. It could be employed as a conditional data for any property simulation which results in a more reliable reservoir characterization in further steps.
A section of an Iranian gas reservoir with six wells was studied to determine the 3D reservoir facies model. Fifteen reservoir facies were first detected along one of the wells with detailed core and thin section descriptions. Due to the significant difference between the core and log data resolution, facies were clustered into four major groups regarding the digenetic processes and petrophyiscal lithofacies properties (permeability and porosity). The lithofacies specification effect on petrophysical properties distribution is usually the only criterion that is considered in conventional simulations. In this paper, however, the diagenetic processes which have a main influence on reservoir properties variation, especially permeability and porosity, have been considered in reservoir facies clustering.
After clustering process, using the available logs and with the help of the neural network, facies distributions along other five wells were also specified. To generate a 3D facies distribution into reservoir scale, SIS methodology was utilized with reference to the previously generated reservoir zonation from sequence stratighraphy, where Acoustic Impedance seismic attribute was set as the secondary data. This attribute was produced by model based inversion method applied in seismic cubes.
Since the diagenetic processes have highly influenced the rock properties of this carbonate reservoir, their effects have been considered as the most important parameter in reservoir facies determination. The ultimate model properly honored each expected sequence cycle properties such as diagenetic processes and lithofacies.
Modelling the Stability of Thin Water Films Using SEM Images
Authors: Frette Olav Inge , Virnovsky George , Hildebrand-Habel Tania 
Published: June 2009

Abstract
Understanding reservoir wettability–including wettability alteration mechanisms–is important to model and to optimise oil recovery. When oil enters an originally water wet porous rock under primary drainage, the oil will gradually displace the water in the pores and a thin water film will be left between the pore walls and the oil. Under certain conditions, the water film may become unstable and collapse. Depending on the chemistry of the oil, water, and porous rock, this collapse may result in wettability alteration. Stability of the water film will control the wettability alteration of the porous rock. Equilibrium saturation configurations in the oil-water system at primary drainage are simulated in 2D for a realistic pore space geometry obtained directly from high resolution scanning electron microscope images and thus retaining geometric features of the porous rock under consideration. The eventual collapse of the wetting phase film is controlled by the curvature of the surface and the disjoining pressure isotherm. Given the critical disjoining pressure value depending on the temperature and the chemical properties of the system at hand, the model facilitates computation of the "wettability index", i.e., the fraction of the rock surface which will come in direct contact with oil and hence potentially become oil wet. Both synthetic and realistic images are analysed. The generic studies show the influence of the surface roughness of the pore walls on the fraction of the surface which can potentially be converted to oil wet for different drainage pressures.
Model-Based Integration and Optimization – Gas Cycling Benchmark
Authors: Juell Aleksander , Whitson Curtis H. , Hoda Mohammad Faizul 
Published: June 2009

Abstract
A benchmark for computational integration of petroleum operations has been constructed. The benchmark consists of two gas-condensate reservoirs producing to a common process facility. A fraction of the processed gas is distributed between the two reservoirs for gas injection. Total project economics are calculated from the produced streams and process related costs. This benchmark may be used to compare different computational integration frameworks, and optimization strategies.
The methods of model integration and optimization discussed in this paper are applicable to complex petroleum operations where it is difficult to quantify cause-and-effect without comprehensive model-based integration. A framework for integration of models describing petroleum operations has been developed. An example test problem is described and studied in detail. Substantial gains in full-field development may be achieved by optimizing over the entire production system.
All models and data in the benchmark problem are made available so that different software platforms can study the effects of alternative integration methods and optimization solver strategy. The project itself can, and probably should, be extended by others to add more complexity (realism) to the reservoir, process, and economics modeling.
Application of the Monte Carlo Simulation in Calculating HC-Reserves
Authors: Komlosi Zsolt , Komlosi Julia 
Published: June 2009

Abstract
One of the key features of E&P companies is their proved reserves in hydrocarbon deposits. Reserve estimation requires knowledge of Initial Hydrocarbon in Place, technical reserves and economic conditions including annual cash flow estimation in the forecast period. Since all parameters used in evaluation procedure are burdened by rather more than less certainty. Therefore, in a sophisticated evaluation process, there should be determined not the expected values only (deterministic way), but errors/uncertainty of estimation as well (stochastic way) applying Monte Carlo simulation.
The estimation procedure comprises three main stages (the third stage /economic modeling/ is not discussed in this paper). In the first stage, key input data (e.g., area, thickness, porosity, and so on) are treated as statistical variables, and the result of the simulation is probability distribution function of HCIIP. This is an input of next stage.
In the second stage technical reserves (recoverable resources) should be estimated. There could be several assumptions for production procedure for a reservoir (as e.g., drive mechanism, hydrodynamic system, phase behavior of reservoir fluids, well spacing, water injection, presence of pressure barriers etc). Each regime (i.e. scenario) can be modeled applying input parameters as statistical variables. This method is named a multiscenario method in the literature. Simulation result for each scenario is a probability distribution function (PDF). While, expected value of PDF reconstructs the deterministic result and gives a basis for project evaluation, the "width" of PDF is proportional with uncertainty of the estimation. Estimating probability of each scenario a combined technical reserve PDF can be derived. Its first percentile can yield proved reserve for booking procedure after economic limit test.
Authors show some case histories how to apply method after a brief theoretical summary referring to SPE-PRMS accepted.
Mature Oil and Gas Assets: From Securing Resources to Maximising Reserves and Production
Authors: Ondracek Walter , Liebl Werner 
Published: June 2009

Abstract
Mature oil and gas fields have been prudently and successful operated since decades by asset teams securing booked reserves, preserving aging facilities and continuously improving performance indicators like costs per barrel or barrels per employee.
However, the operating mode has been rather conservative with respect to resources employed to increase production capacities and ultimate recovery.
Today, with peak oil as a realistic threat and the hectic quest for more oil and gas reserves, oil companies need to change their strategy. Expected high oil prices support such a change, and aging surface facilities force us to change fast.
The paper summarizes how we went about defining the basis for the required change in OMV/PETROM. It is about defining success criteria which go beyond technology and set the framework right for the implementation of sustainable field re-development projects to maximize capacities and recoveries.
Increasing the Capacity of an Underground Gas Storage by Optimized Well Completions, Matzen Field, Austria
Authors: Florian Thomas , Ueberer Wolfgang , Nederlof Eduard 
Published: June 2009

Abstract
This paper presents an overview of methods and technologies, OMV Austria has already implemented and plans to introduce in Underground Gas Storages (UGS) to improve the performance of single wells and thus to increase the total capacity of the UGS.
Since 1968, OMV Austria operates six UGS in the Matzen Field, located in Lower Austria near Vienna, and one UGS in Upper Austria.
The depths of these former sandstone gas reservoirs vary from 550 to 1,200 m. At the moment, the maximum working gas volumes (WGV) equals 2.33 billion m3. Withdrawal and injection is mainly achieved with 150 former gas production wells. Most of the existing wells are equipped with sand control completions. Well tests have shown that moderate to high skins are present. Nevertheless, withdrawal rates of about 15,000 m3/h per well can be achieved.
The increasing demand for gas initiated the necessity to improve the capacity of OMV's underground gas storage operations. Additionally, reservoir studies of all seven gas storage reservoirs indicated a potential for cost savings by reducing the number of active wells. Furthermore the reservoir models identified optimum well locations for infill drilling operations. In order to execute this strategy, the following measures have been worked out: Existing wells were converted to high-capacity wells by replacing Inside Casing Gravel Packs (ICGP) by Open-Hole Gravel Packs (OHGP)Drilling of two new high-capacity horizontal wells completed with an OHGP and Expandable Sand Screen (ESS).Increasing the maximum operating pressure in the underground gas storage reservoir
For two newly drilled wells, state of the art completions were chosen. By installing a horizontal open-hole gravel pack in one well, and an ESS in the other, rates of up to 50,000 m3/h/well can be reached. Re-placing old ICGP's by OHGP led to increased withdrawal rates of up to 35,000 m3/h per well.
For both, the re-completions and the new wells, a state of the art mud system (drill-in fluid and workover fluid, respectively) was used for the first time in gas reservoirs.
However, the most economical way to improve the capacity of underground gas storage is to increase the working gas volume. Currently the working gas volume is limited by the initial reservoir pressure (=maximum operating pressure). At the moment, OMV Austria is preparing a study to get the allowance for increasing the maximum operating pressure in two underground gas storages. This could add another 300 million m3 of working gas volume.
Injection of Supercritical CO2 into Deep Saline Carbonate Formations, Predictions from Geochemical Modeling
Authors: Taberner C. , Zhang G. , Cartwright L. , Xu T. 
Published: June 2009

Abstract
Modeling of supercritical CO2 injection into a deep saline aquifer from a carbonate formation (calcite and dolomite, with minor anhydrite) was performed using TOUGHREACT (Xu et al. 2006) with Pitzer ion-interaction model implementation for handling high salinity problems (Zhang et al. 2006). The formation brine salinity is ~225,000 ppm (NaCl dominant), temperature at 102°C and pressure at 225 bars. CO2 injection rate was considered constant for a period of 1 year through a horizontal well in a 3D model domain. The carbonate formation was assumed to have homogeneous porosity and permeability and to be overlaid by an impermeable seal. The effect of a higher permeability fault with orientation perpendicular to the horizontal well, and bounded by the impermeable overburden, was evaluated. The impact on mineralogical and rock property changes in the saline aquifer during injection has been assessed. The simulations found that: (1) the higher permeability fault acts as a CO2 conduit; (2) a dryout zone is developed within a few meters from the injection well due to displacement by supercritical CO2 and dissolution of water into CO2 stream (3) at the front of the dryout zone, brine is further concentrated due to water dissolution into CO2, pH is lowered from 5.5 to 3.1, halite (NaCl) and anhydrite (CaSO4) precipitate, and the brine becomes CaCl2–dominant; (4) near well-bore porosity reduces by ~5%-17% due to halite precipitation (dryout zone); (5) HCl gas is generated from the dryout front; (6) calcite and dolomite dissolve as the CO2 plume advances during injection; (7) anhydrite, however, slightly dissolves along the CO2 front, but precipitates in the area corresponding to the CO2 plume with higher proportions near well-bore. These findings are valuable for the assessment of injectivity changes and near well-bore stability of saline aquifers in carbonate formations during injection of CO2. The overall mineral trapping in hundreds of years is not the focuss of this paper. However, from ongoing modeling experiments, mineral trapping is anticipated to be not significant for the mineralogies and brine chemistries and salinities of the carbonate formation under assessment. This study method is useful for the further evaluation of engineering options to enhance immobile trapping of CO2 and mitigation measures for potential injectivity impairment.
Uncertainty Reduction By Production Data Assimilation Combining Gradual Deformation With Adaptive Response Surface Methodology
Authors: Busby Daniel , Feraille Mathieu , Gervais Veronique 
Published: June 2009

Abstract
We propose a workflow to reduce initial uncertainty of the reservoir model by incorporating production data. Advanced statistical methods such as sensitivity analysis, Gaussian process response surfaces, sequential experimental design and gradual deformation are combined to produce a very cost effective approach to production data assimilation. In previous works, response surface and experimental design methods have been proven quite effective for uncertainty propagation workflows; however they were only able to deal with continuous and discrete parameters. By using the gradual deformation method we are able to include stochastic parameters such as permeability and porosity, thus avoiding previous limitations. The advantages of using advanced non-parametric response surface methods are highlighted both in obtaining accurate global sensitivity indices and also to apply a full probabilistic inversion approach. Note that both methods generally require several thousands of model runs and are therefore unpractical without using response surface methods. Statistical diagnostics are used to validate the response surface models and adaptive sequential design strategies are proposed to improve their accuracy.
The workflow is applied to production data assimilation of a Brazilian oil field. In a first phase the production history mismatch is analyzed to understand the general behavior of the model as well as to select the uncertain parameters mostly responsible for this mismatch. To perform this phase experimental design and sensitivity analysis techniques are used. In a second phase another objective function is built using only data that seem to be possibly matched using the current model and set of parameters. The new objective function is used in a probabilistic inversion loop to obtain posterior distribution of parameters and to reduce the forecasting uncertainty. The results of the study can then be directly used to obtain reliable probabilistic forecasts. Moreover, posterior distributions of parameters can be utilized to reduce uncertainty ranges in a subsequent study with the updated geological model.
Real Time Integration of Reservoir Modeling and Formation Testing
Authors: Gisolf Adriaan , DUBOST Francois , ZUO Julian , WILLIAMS Stephen , KRISTOFFERSEN Julianne , ACHOUROV Vladislav , BISARAH Andrawiss , MULLINS Oliver C. 
Published: June 2009

Abstract
The increasing complexities of newly discovered reservoirs coupled with the increasing cost structure of field development mandate significantly improved and timely work flows for reservoir evaluation. Traditional modeling workflows are typically time consuming and require well organized cross disciplinary integration between geoscientists. Such models and processes are not well suited to be used and updated during formation evaluation acquisition phases of field development. In this paper a more accessible approach is proposed and demonstrated. The existing fluids model is combined with the current geologic model to construct an accurate representation of key features of the reservoir. This model is then used to predict data for a wireline formation sampling and testing tool (WFT), with emphasis on downhole fluid analysis (DFA). In this process, current reservoir understanding is tested by direct measurement in real time. If differences are uncovered between predicted and measured log data, the WFT tool is in the well, and measurements can be made to uncover the source of the error.
In this paper a workflow is demonstrated where WFT DFA and PVT lab reports were used to build a fluid model after the first exploration well data was acquired. This model was then used to predict fluid properties and WFT DFA logs for a subsequent well intersecting nominally the same compartment. These DFA predictions presumed fluid equilibrium and flow connectivity. Real-time comparisons were made of predicted and measured pressures, fluid gradients, contacts and DFA data obtained from the WFT logging run. Agreement of predicted and measured log data indicates that fluid properties and reservoir connectivities used for the modeling are correct. If predictions disagree with measurements the acquisition program can be altered in real time to ensure sufficient data is acquired to understand the reservoir model inaccuracies.
During the WFT logging job, this predictive model enabled validation of critical WFT data. This process also allowed testing of the reservoir connectivity. It was discovered that either compartmentalization or lateral disequilibrium of the fluids in the reservoir exists. Interpretation of the DFA data suggested that a subtle lateral disequilibrium exists and the assumption of reservoir connectivity is supported.
Comparison Between Smart And Conventional Wells Considering Uncertainties
Authors: da Silva João Paulo Q. G. , Schiozer Denis J. 
Published: June 2009

Abstract
The selection of a production strategy is one of the most important tasks to ensure success of petroleum fields development. In order to improve the performance of fields, the use of smart wells is becoming a common practice. In such wells, devices like valves and sensors are able to monitor and control the production, in real time, adding flexibility to the operation. However, it is possible that the expected gain of these wells production does not pay off the required additional investments. Thus, the aim of this research is to compare the differences between smart and conventional well performances.
A methodology of production strategy optimization, which considers the availability of different platforms, each one with a particular fluid treatment capacity, was developed and applied to both the conventional and smart wells. Special care was given to some details of the methodology in order to guarantee a fair comparison between the two options. The methodology was applied to a heterogeneous reservoir, considering a deterministic case. After it, the sensibility of the model was studied by changing geological characteristics, adding uncertainties to the problem.
The optimization results showed small differences between the two alternatives. Consequently, smart wells were able to improve oil production and reduce water production but the net present value (NPV) indicated that the use of conventional well was, in average, slightly more advantageous. Also, the application of different platforms with different capacities induced changes in the performance of the two kinds of wells. Finally, a sensitivity analysis and a detailed discussion were made in order to study situations where the smart wells could be applied.
With the developed methodology, it was possible to carry out a fair comparison between the smart and conventional wells, providing good confidence and efficiency in the optimization process.