bluuebunny/crossref_metadata_2025_split huggingface dataset:
Success and Challenges in Gathering Dynamic Data in Tight Gas Condensate Fields - Lessons Learnt
Authors: Urquhart M. A. , Harrasi M. 
Published: September 2013

Abstract
In 2009 PDO started an ambitious tight and deep gas exploration programme, exploring for previously untapped reservoirs, both conventional tight gas plays as well as deep unconventional gas resources. These resources are typically in previously undrilled formations at great depths, highly overpressurized with high temperatures, and uncertain fluid fill and composition. The unique geological properties of these reservoirs require different strategies to acquire the necessary data to enable the assessment of fluid compositions, permeability and well productivity data that are essential input to development decisions.
The acquisition of formation permeability and productivity data is very challenging in these environments; the paper will demonstrate how well-testing data has been used to gather information on fluid flow characteristics and dynamic properties where hydraulic fraccing is routinely used to achieve commercial production rates.
Hydrocarbon saturation and fluid contacts tend to be highly uncertain in tight gas reservoirs, this paper demonstrates strategies to gather information on likely fluid content of reservoir zones during the exploration and appraisal stage. Acquisition of representative fluid samples for PVT purposes is also extremely challenging in these type of reservoirs and this paper will outline the success and challenges experienced to date in the North Oman Area, and illustrates examples where good quality samples have been recovered.
A New Method of Numerical Simulation for Viscoelastic Polymer Flooding
Authors: Wang Z. B. , Wang Q. , Ma D. S. , Ye Y. Z. , Liu Z. X. 
Published: September 2013

Abstract
Currently, polymer flooding can further improve oil recovery more than 10 percent on the basis of the water flooding in China. Many substantial indoor experiment results have shown that polymer flooding can significantly improve oil recovery because it can improve both sweep efficiency and oil displacement efficiency. Most of the current researches are from the indoor experiment by the ways of description on the rheological characteristics and the flow characterization of polymer solution in porous media. These kinds of research usually involve many parameters. However, it is very difficult to establish the polymer flooding mathematical model by the parameters from indoor experiments. So, the three mainstream percolation model describing the characterization of polymer viscoelastic flooding mechanism are reviewed respectively at first, such as synthetical resistance coefficient category, effective seepage viscosity category and residual oil reduced by normal stress category. Then taken the imperfections of current models as breakthrough, a new mathematical model with full consideration of polymer solution's viscosity and elasticity is established. After that, the corresponding numerical simulation program is completed. All the parameters in the model have clear physical meaning. Among these, characteristics of sweep volume expanded by the polymer solution's viscoelasticity are influenced by its solution properties, injection speed and reservoir pore structure; characteristics of oil displacement efficiency improved by its elasticity are considered by first normal stress difference under different shearing rate conditions. Comparing to relatively conventional mathematical models which only take polymer's viscous flooding mechanism into account, the new model can truly describe the oil displacement mechanism and production increasing effect of polymer flooding in a more comprehensive way. For the future, the establishment of the new simulation method can lay a good foundation for in-depth study on polymer flooding mechanism and its large-scale promotion and application.
Analytical Models for Well Test Analysis in Class 3 Gas Hydrate Reservoirs
Authors: Kome M. , Amro M. , Cinar Y. 
Published: September 2013

Abstract
Well testing in gas hydrate reservoirs is challenging due to the complexity of reservoir behavior. Gas hydrates dissociate when the bottom-hole flowing pressure drops below the hydrate equilibrium pressure, a phenomenon also seen in CBM reservoirs below desorption pressures. Relative permeability of reservoir fluids keeps changing at the dissociation front, depending on the prevailing reservoir pressure, a phenomenon also seen in gas condensate reservoirs. If transient rate and pressure behavior of the hydrate formation are to be interpreted accurately, the analytical model for interpretation should consider both phenomena. This makes well testing in these reservoirs more challenging, not forgetting the multiphase flow and the endothermic dissociation of hydrates during pressure drawdown. This implies a continuously changing bottom-hole flowing temperature for every bottom-hole flowing pressure, unlike what is seen in conventional gas reservoirs.
This paper presents new analytical models for well testing in class 2 gas hydrates. The heat consumption during hydrate dissociation, activated by a pressure depression, requires heat transport models to be incorporated in the diffusivity equation. By combining mass balance and energy balance techniques, a representative diffusivity equation for the reservoir behavior is derived. Constantly changing reservoir temperature, relative permeability and reservoir fluid properties make it imperative to use pseudo-pressure integrals to describe flow. The analytical solutions to the model are represented both for constant rate and constant pressure conditions for pressure transient and rate transient analyses, respectively. By expressing the analytical model in terms of dimensionless pseudo-parameters and considering the presence of free mobile fluid, for the constant terminal rate case, solutions provided van Everdingen et.al, Hantush et al., Jaeger et al. are implemented.
Due to the dependence of hydrate dissociation on the bottom-hole flowing pressure, constant pressure solutions provide a good tool for investigating the reservoir behavior through rate transient analysis. With further simplifications of the numerical approximations of the constant pressure solution provided by Erdwardson et al., semilog and diagnostic plots could be made.
Solutions to the constant rate and pressure are presented in this paper. A more general equation equation for rate decline analysis has been developed, with applicability in conventional gas reservoirs. A dimensionless compressibility-mobility function is incorporated in the model which is then related to the Arps decline curve models. Different methods of rate transient analysis are addressed in this paper to identify different reservoir parameters.
Integrated Three Phase Fluid Analysis Approach of PNC in Miscible Gas and WAG Injections of Complex Carbonate Reservoir
Authors: Gibrata Muhammad A , Kalam M Zubair , Mohsen A , Ashraf S , Basioni M , Mahdi Ahmed E 
Published: September 2013

Abstract
A project study has been performed in reservoir saturation monitoring of carbonate reservoir on-shore Abu Dhabi. An integrated three phase fluid approach of pulsed neutron capture (PNC) in miscible gas and water alternating gas (WAG) injection of complex carbonate reservoir is presented. It has utilized open hole logs, production logs, production test, fluid sampling/PVT and core data in workflow analysis. It has been a challenge to get accurate and reliable reservoir saturation during production phase with gas and WAG wells injection in this carbonate reservoir. It's complex reservoir conditions has added the challenge for reservoir saturation monitoring program, evaluation and management.
Standard logs data quality check and correction need to be performed to ensure of consistency in analysis. PNC-Sigma (Σ), reliable lithology and porosity were used in three phase fluid model approach by optimizing simultaneous equation. It optimizes relationship among tools, parameters and formation component volumes. End point PNC-Sigma gas, oil and water have been determined in analysis to get an accurate gas, oil and water saturation. Openhole sigma, resistivity log and special core analysis (Special Core Analysis-SCAL/Digital Rock Physic-DRP) data have been used to evaluate and validate the changing of reservoir saturation. Furthermore multi spinner/probes production logs, water flow log (WFL) would be recommended in horizontal/high deviation production or injection wells along with surface production test to get an accurate of recent fluid contribution of reservoir. Validated well production profile in logged or nearby area has been used for comparison and calibration for the results.
The integration approach of logs, well production/test and core data in particular carbonate reservoir has been used to provide accurate and reliable reservoir saturation results. It has been observed that the identification of miscible gas and water saturation using three phase fluid approach in reservoir has provided a lot of benefit for reservoir monitoring and management in this field. The integration of formation evaluation in this case study has provided improvement, reliability in reservoir saturation results for carbonate reservoir monitoring and management.
Engineering Workflow for Probabilistic Assisted History Matching and Production Forecasting: Application to a Middle East Carbonate Reservoir
Authors: Maucec M. , Singh A. P. , Carvajal G. A. , Mirzadeh S. , Knabe S. P. , Chambers R. L. , Shi G. , Al-Jasmi A. K. , El Din I. H. , Nasr H. 
Published: September 2013

Abstract
Traditional reconciliation of geomodels with production data is one of the most laborious tasks in reservoir engineering. The uncertainty associated with the great majority of model variables only adds to the overall complexity. This paper introduces an engineering workflow for probabilistic assisted history matching that captures inherent model uncertainty and allows for better quantification of production forecasts.
The workflow is applied to history matching of the pilot area in a major, structurally complex Middle East (ME) carbonate reservoir. The simulation model combines 49 wells in five waterflood patterns to match 50 years of oil production and 12 years of water injection and to predict eight years of production. Initially, the reservoir model was calibrated to match oil production by modifying permeability and/or porosity at well locations and by fine-tuning rock-type properties and water saturation. The second level history match implemented two-stage Markov chain Monte Carlo (McMC) stochastic optimization to minimize the misfit in water cut on a well-by-well basis. While relative to evolutionary algorithms or the ensemble Kalman filter (EnKF), the McMC methods provide a statistically rigorous alternative for sampling posterior distribution; when deployed in direct simulation, they impose a high computational cost. The approach presented here accelerates the process by parameterizing the permeability using discrete cosine transform (DCT), constraining the proxy model using streamline-based sensitivities and utilizing parallel and cluster computing.
While probabilistic assisted history matching (AHM) successfully reduced the misfit for most producing wells, the computational convergence was sensitive to the level of preserved geological detail. The optimal number of representative history-matched models was identified to capture the uncertainty in reservoir spatial connectivity using rigorous optimization and dynamic model ranking based on forecasted oil recovery factors (ORFs). The reduced set of models minimized the computational load for forecast-based analysis, while retaining the knowledge of the uncertainty in the recovery factor.
The comprehensive probabilistic AHM workflow was implemented at the operator's North Kuwait Integrated Digital Oilfield (KwIDF) collaboration center. It delivers an optimized reservoir model for waterflood management and automatically updates the model quarterly with geological, production, and completion information. This allows engineers to improve the reservoir characterization and identify the areas that require more data capture.
Well Inflow Modelling for Wells Not Aligned to a Numerical Grid
Authors: Egberts P. J. , Shatyrbayeva I. , Fokker P. A. 
Published: September 2013

Abstract
In numerical reservoir simulation practise the orientation of the spatial grid is often dictated by geological features of the reservoir model. As a consequence the trajectory of, in particular, a horizontal or slanted well or a well with a complex geometry, possibly with multilaterals, generally is not aligned to the numerical grid. This situation may lead to significant numerical artefacts, as an irregular inflow profile along the well. Although the total flow rate of the well may be reasonably accurate, a non-smooth profile is unwanted if the simulator is coupled to a dedicated wellbore flow model. Another artefact occurs if the ratio of the vertical to horizontal permeability is small (i. e. kv/kh&lt; 0.001): standard models result in an overestimation of the total flow rate.
Well inflow modelling relates the so-called well index, the ratio between well rate times viscosity and the difference between the well pressure and the gridblock pressure, to quantities such as gridblock dimensions and permeability. The origin of the numerical issues is the limitation of the well index estimation as proposed by Peaceman, and generalised by Alvestad for wells not aligned to the grid.
We combined simulation results of a semi-analytic model and simulation results from a dedicated numerical simulation to calculate so-called semi-analytical well indices. We demonstrate that by using these semi-analytical well indices in a numerical reservoir simulator the aforementioned issues are resolved. The semi-analytic model that has been used solves the equation for steady state flow in 3D for line sink(s) with variable influx. The variable influx is then exploited to approximate a uniform pressure condition along the wellbore. This modelling approach allows for a complex geometry of the well such as a multilateral.
To arrive at a practical implementation of our method we propose to use the standard well index along with a corrective skin factor based on our approach. Correlations for such a corrective skin factor then need to be developed based on a great number of well scenarios, anisotropy ratios and grid aspect ratios.
Rock-typing using the complete set of additive morphological descriptors
Authors: Ismail Nurul Izza , Latham Shane , Arns Christoph H. 
Published: September 2013

Abstract
The mechanical and transport properties of reservoir rocks depend on the morphology of microstructure, e.g. connectivity, size and shape of grains and of the pores. Such information can be gained from digital core analysis, which is increasingly used to understand the internal fabric of heterogeneous rocks or for the analysis of samples not amenable to standard laboratory analysis. At the same time, big advances are made on the imaging hardware side including the development of ultra-high resolution CCDs and recording techniques like helical scanning, leading to datasets of enormous dimensions and relatively large field of view. In this context it is highly desirable to develop automatic coarse scale classification methods to e.g. recognize the occurrence and spatial structure of digital rock types within such tomographic images - or existing morphological trends within a rock type, as this may lead to powerful characterization and data reduction techniques as well as upscaling methods.
We use regional Minkowski measures to define fine-sale rock types using a multi-variate Gaussian mixture model for classification. The discriminative power of the method is firstly demonstrated for an artificial sample which consists of a mixture of Poisson processes spatially separated using a Gaussian random field approach. Furthermore, we demonstrate how this method can be used to describe the fractions of two spatially overlapping non-stationary process generating a morphological trend - e.g. a fining up sequence. Finally, the method is applied to discriminate different morphological regimes of a thin- bedded sandstone. Importantly, for morphologies resulting from a Poisson process of grains, the classification result can directly be used to predict physical properties using effective grain shapes. For other processes such a relationship may be developed; in particular, using the classification result subsections of a tomogram can be selected for which such a relationship can be derived explicitly.
Pore-Scale Visualisation of Two-Phase Fluid Displacement Processes in a Carbonate Rock using X-ray micro-Tomography Technique
Authors: Pak Tannaz , Butler Ian B. , Geiger Sebastian , van Dijke Rink , Jiang Zeyun , Elphick Stephen , Sorbie Ken 
Published: September 2013

Abstract
The physics of multi-phase displacement processes in the individual pores of a connected pore-network of a rock ultimately controls how oil, gas and water move in reservoir rocks and how readily they can be produced. These pore scale processes, including piston-like displacement, snap off, film-flow and fluid redistribution have been studied traditionally in pore-network simulations as well as in 2D micro-model experiments. However, recent advances in X-ray computed micro-tomography (CT) techniques now enable us to visualize and monitor these processes in 3D during in-situ core flooding experiments at pore-scale resolution. This provides new information on the spatial and temporal evolution of oil and water phase clusters and films.
In this paper, we present results of a suite of two-phase fluid displacement experiments performed on a dolomite core plug. The experiments consist of a series of fluid injections and in-situ CT scans of the core in certain time steps during the drainage and imbibition displacement processes. The fluid phases are brine and a mineral oil. A simple, low-cost and highly X-ray transparent design for core flooding cells is introduced.
Our experiments and CT images allow us to visualize the 3D fluid structures of each phase during fluid displacements in carbonate rocks with excellent clarity. Piston-like displacement and snap off mechanisms have been captured clearly in 3D. In addition, the formation, collapse and reorganisation of brine films surrounding oil blobs in individual pores were clearly visualised. However, the formation of oil films, which could provide connectivity for the hydrocarbon phase at low saturations, could not be observed in these experiments. The observed displacement processes and the particular oil-water/rock configurations seen in the displacements suggest the rock is preferentially water wet.
Impact of the Spatial Correlation of Microporosity on Fluid Flow in Carbonate Rocks
Authors: Jiang Zeyun , van Dijke Marinus I. , Geiger Sebastian , Kronbauer Denise , Mantovani Iara Frangiotti , Fernandes Celso Peres 
Published: September 2013

Abstract
Pore-network modelling, or digital petrophysics, is an emerging technology which allows computing physically consistent two- and three-phase flow functions such as relative permeability and capillary pressure curves at arbitrary wettability. Considering the difficulty in measuring these functions reliably in the laboratory, pore-network modelling is increasingly used to guide and complement costly and time-consuming SCAL programmes. Although pore-network modelling is now well-established for clastic reservoirs, applying it to carbonate rocks is significantly more challenging due to their complex and multi-scale pore structure, comprising micro- and macro-pores as well as cracks and fractures. We have hence developed a novel method to integrate pore-networks, which have been extracted at multiple scales directly from CT images at different resolutions, into a single pore-network model that can be used in subsequent calculations of two- and three-phase flow functions. This method has been validated by comparing computed two-phase relative permeability and capillary pressure curves for a multiscale network to the corresponding laboratory measurements. However, in this approach it is important to accurately consider the impact of the spatial distribution of fine network elements, which are extracted from high-resolution images. We therefore show the impact of the spatial correlation of high-resolution porosity on single- and two-phase fluid flow and propose a model that allows us to simulate the spatial correlation between coarse-scale pores and fine-scale porosity in the absence of a suitable CT image that segments the rock into three phases (pores, sub-resolution matrix porosity, and solid). We demonstrate the impact of the spatial correlation of microporosity on absolute and relative permeabilities by applying this model to various datasets, including CT images of an off-shore carbonate reservoir. This demonstrates that the spatial correlation of microporosity is one of the key factors controlling recovery from carbonate reservoirs and that our new method allows us to quantify it.
Evaluating Injection Performance With High-precision Temperature Logging And Numerical Temperature Modelling
Authors: Aslanyan Arthur , Wilson Michael , Al-Shammakhy Abdullah , Aristov Sergey 
Published: September 2013

ABSTRACT
The paper shows how high-precision temperature (HPT) logging and numerical temperature modelling for radial flow injection (TERMOSIM) assess the performance of water injection wells, and outlines specific features of modern temperature logging tools and logging procedures. The basic principles and critical elements of temperature modelling for injection wells are discussed. The paper presents five cases illustrating how the fitting of a numerical model to actual temperature logs can be used to describe the injection pattern including complicacies caused by behind-casing channelling. Particular attention is given to how temperature logging and modelling complement information obtained by the conventional PLT technique based on the mechanical spinner. The concept and basic features of the TERMOSIM temperature modelling software are given in the Appendix.