bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Resolution Numerical Simulations of Capillary Trapping for Carbon Dioxide in Fractured Formations
Authors: Annewandter R. , Main I. , Geiger S.
Published: September 2013

CO2 injection is one of the most common forms of enhanced oil recovery. It also allows us to sequester greenhouse gases in the subsurface. CO2 injection is currently considered for many clastic and carbonate reservoirs. The latter reservoirs often contain fractures, therefore quantification of sweep efficiency and CO2 trapping in fractured formations is of critical importance to design appropriate CO2 injection schemes for carbonate reservoirs.

Discrete fracture and matrix (DFM) simulations have emerged as a powerful technology to analyse the fundamental flow and transport properties in naturally fractured reservoirs and bridge gaps between geosciences and reservoir engineering: they help to validate upscaling workflows, improve the analysis of pressure transients from well-tests, and allow to explore how uncertainties in fracture network properties impact hydrocarbon recovery. The key difference between DFM simulations and traditional dual-porosity approaches is that the structurally complex fracture geometries are explicitly discretised as 2D surfaces in a 3D reservoir model, which hence comprises a geologically realistic representation of the fracture patterns and rock matrix.

Here we extend the DFM simulation workflow to account for capillary trapping of CO2 in fractured media. Fluid flow is described by a fully compositional model including an equation of state for CO2-H2O-NaCl fluids. The governing equations are discretised in space using unstructured and mixed-dimensional finite element - finite volume techniques. We demonstrate how our new DFM approach can be applied to simulate CO2 injection and trapping of CO2 in fractured geological formations with geologically realistic fracture networks. We show how matrix diffusion and capillary forces influence the rate at which CO2 is trapped in the rock matrix and discuss how this trapping could be modelled more accurately in conventional reservoir simulators.
Fast-Track Modeling Approach: An Alternative Workflow for Reservoir Simulation Modeling
Authors: Al-Jenaibi Faisal , Lacroix Sebastien , Meziani Said , Bugio Shamsudin , Ben Salem Ryadh
Published: September 2013

The oil and gas industry has a long history of model construction relying on the integration on multiple disciplines including seismic, sedimentology, geology and petrophysics. It is undeniable that all steps are required to lead to a good characterization of the studied reservoir and to provide reliable and realistic predictions. However the necessary time to finalize each step often leads to a modeling process of several years. This paper therefore discusses an alternative workflow, or Fast-Track modeling approach, which allows generating a representative and matched reservoir model in a considerably reduced time. This approach consists in: Using in-house technology for porosity/permeability prediction and property population.Introducing a new capillary pressure design and dynamic rock-typing concept.Using automated history matching tools to fine tune the match at the well level.

This workflow ensures achieving a better petrophysical properties consistency between logs, cores and models, a more representative asset volume estimates and also prevents utilization of non-measured parameters such as irreducible water saturation (Swc's) or unproven and extensive permeability multipliers. This altogether contributes in reducing convergences problems as well as providing more consistent dynamic model setup.

This workflow was applied on a complex offshore reservoir consisting of a large gas cap and significant oil rim. The results and achievements are presented within this paper and demonstrate the suitability of this workflow as a short term alternative and shortcut to complex simulation modeling, in waiting of all adequate studies to be completed and integrated in a detailed reservoir model.
Improved Reservoir Surveillance through Injected Tracers in a Saudi Arabian Oil Field: Case Study
Authors: Ali Almosa Muhanad , Zaberi Husain , Huseby O.
Published: September 2013

High-quality reservoir characterization, improved reservoir dynamics, optimized water flooding and better understanding of fluid movements are some key factors for successful reservoir management. Interwell tracer test (IWTT) technology has been recognized as an efficient tool to determine fluid pathways between wells and evaluate areal water breakthrough between injectors and producers, along with estimating the velocities at which the injected water is breaking through, and these can be integrated in the geological and reservoir models of the field to reduce uncertainties attributed to fluid flow mechanism and interwell communication.

This paper presents a case study of IWTT technology application in a heterogeneous reservoir in a Saudi Arabian oil field and shows how this characterization tool was utilized to investigate the reservoir flow mechanism; and how the derived information facilitated a better reservoir management through improved reservoir monitoring and enhanced understanding of reservoir fluid dynamics. The project commenced in November 2007 through injecting unique chemical tracers into a set of injectors to effectively monitor injected fluid movement in the reservoir, after which tracers were continuously monitored through yearly sampling programs by collecting samples from adjacent oil producers.

The results of the project will be showcased on how it has provided valuable insights through identifying interwell pathways, estimating velocities at which tracers are traveling and optimizing water injection volumes. These findings were translated in optimized reservoir management, resulting in a tangible impact of the offset wells’ productivity and sustainability.
Optimisation of Smart Well Completion Design in the Presence of Uncertainty
Authors: Ghosh Baijayanta , King Peter
Published: September 2013

Intelligent/smart completions are widely used to maximize the value of production wells through higher ultimate hydrocarbon recoveries, to promote better clean-up of unconventional wells during ‘flow-back’ and to improve sweep efficiency in case of injector wells. To maximize the economic value of these applications, especially in the presence of uncertainties (geological, reservoir and long term tool reliability) and minimize the economic risk it's vital to optimise the placement and operational settings of the Interval Control Devices (ICDs)/AICDs (Autonomous Inflow Control Devices)/Interval Control Valves (ICVs). The requirement for optimisation could also arise from the limitation imposed by present technology on the maximum number of valves deployable in a single completion string.

In this paper an optimisation routine for determining the optimal placement of Interval Control Valves (ICVs), and their inflow settings is presented. The overall optimisation scheme uses the simulated annealing algorithm in conjunction with a commercial reservoir simulator to maximize an objective function that captures the mean and variance in the well's estimated value. Multiple geostatistical realizations are used to incorporate the element of geological/reservoir uncertainty in the optimisation process. The workflow also accounts for the risk of flow control valve failure. A brief description of the screening methodology (to choose the appropriate inflow control technology) and a decision analysis framework for deploying intelligent completion technology, based on utility theory, is also presented herein.

The optimisation technique was applied to cooptimise the positions and flow cross-section areas of the ICVs in a horizontal well, completed in an oil reservoir using a composite objective function. Geologic/reservoir and valve-life uncertainties were incorporated in the routine. The improvement in the well's Net Present Value (which is between 55–70% for the cases investigated) obtained through the employment of this technique, is also illustrated. An instance of the decision analysis is carried out to exhibit the suitability of intelligent completions deployment in the given well.
Multilevel Preconditioners for a New Generation Reservoir Simulator
Authors: Wu Shuhong , Xu Jinchao , Zhang Chen-Song , Li Qiaoyun , Wang Baohua , Li Xiaobo , Li Hua
Published: September 2013

As a result of the interplay between advances in computer hardware, software, and algorithms, we are now in a new era of large-scale simulation. Fine-scale reservoir simulations focus on fine reservoir characterization, accurate flow description, efficient nonlinear and linear solvers, and parallel implementation. In this paper, we discuss a multilevel preconditioner in the new-generation simulator HiSim developed by RIPED, PetroChina. This preconditioner relies on the method of subspace corrections (MSC) to solve large-scale linear systems arising from fully implicit methods in reservoir simulations. Unlike traditional purely algebraic methods, the proposed preconditioner takes into account some of the properties of pressure, saturation, and implicit well variables. We investigate the efficiency and robustness of the proposed method by applying it to a million-cell benchmark problems, and a real-world matured reservoir with high heterogeneity, high water-cut, geological faults, and complex well scheduling. The numerical results indicate that the proposed method is robust with respect to the heterogeneity, anisotropy, and number of wells.
Integrated Workflow Towards Characterizing Hydraulic Fractures in Tight Gas Reservoirs-Modeling, Uncertainty Analysis, History Matching & Production Forecasting
Authors: Thomas Tony , Belova Natela , Goloborodko Andrey
Published: September 2013

This paper details real field case of an integrated approach followed in near wellbore modeling with the aim of characterizing hydraulic fractures in tight gas reservoirs. Uncertainties in the geology, inability to draw conclusions from data obtained and how to effectively integrate data from different sources (cores, logs, geological model, well test & production data) were the challenges.

The steps taken to overcome these challenges and addressing the uncertainty, using both analytical and numerical modeling, resulting in improved well and reservoir characterization, is presented in this paper.

The work done and outlined in this paper provides an integrated workflow for fracture modeling and performance prediction through a probabilistic approach.

The work involves: –Analyzing and incorporating the data and their uncertainty from varied sources.–Generating multiple realizations of the static model.–Selection of the appropriate static model based on an error function.–Near wellbore modeling to account for hydraulic fracture.–Probabilistic Model validation by replicating the well testing sequence.

This integrated workflow provided enhanced fracture characterization and performance prediction while incorporating the impacts of uncertainty. Reservoir structure and depositional environment understanding were improved.

In tight gas reservoirs in the early stage of development this approach is more comprehensive towards modeling hydraulic fractures parameters and hence production optimization from the reservoir. The value information gained from this workflow is then integrated into the full field dynamic model.
Seismic Attribute Utilization for FFDP Well Placement Optimization, Upper Cretaceous Fractured Complex Carbonate Reservoir, Onshore Oil Field, U.A.E.
Authors: Mahmoud Sabry L. , Hozayen Magdy , Radwan El Sayed
Published: September 2013

An Upper Cretaceous carbonate reservoir, onshore oil field in Abu Dhabi is characterized by its vigorous surface topography and subsurface complex structural setting. The studied reservoir is a highly fractured elongated anticline trending NE-SW. Fracture occurrence and distribution have influenced the reservoir performance in terms of oil production and water cut from the field. Seismic attributes integrated with well log data and well performance have provided a good understanding of the lineament/fracture distribution within the reservoir. In addition, this integration enhanced the Full Field Development Plan (FFDP) optimization in terms of well placement and reservoir performance to avoid early water break through (EWBT) due to fractures. 3D seismic data was acquired with high fold and wide azimuth over the field in 2007. The 3D seismic data was processed in 2008 with some processing issues. In 2012, new algorithms were applied over a pilot area in order to resolve the processing issues and to preserve relative true amplitude for further reservoir characterization purposes. The pilot products have better identified short falls in the 2008 processed data. Seismic attributes were analyzed and the interpreted lineaments/fractures distribution will help better understand fracture orientation and their impact on oil production and water cut for full field development. The Seismic attributes successfully captured additional information and guided the well planning to avoid the highly lineament/fractured area. In addition, the new identified fracture system provides essential information for the ongoing and future development plans for this field. This 3D seismic input for fracture detection and well trajectories optimization resulted in better well performance and delay of water production especially in mid flank wells. The preliminary results of the attribute extraction at the reservoir targets are encouraging and new 3D seismic reprocessing data is considered a potential solution for the quantitative seismic interpretation and the reservoir characterization which achieved optimum well locations and orientation in this complicated onshore field.
Multiscale Characterization On The Pore Network In Carbonate Rocks
Authors: Solling Theis , Marquez Xiomara , McKay Thomas , Fogden Andrew
Published: September 2013

The flow properties of carbonate reservoir rocks depend on the pore and throat shape (geometry), the way they are interconnected (topology) and on the forces associated with the fluid-rock interactions (wettability). Little quantitative information on these parameters and their dependencies are currently available. We present the preliminary results of an on-going multiscale study of carbonate rocks which integrates classical diagenetic characterization of their pore system with 3D visualization and analysis of its structure (from micro-CT imaging) and mineral and elemental surface composition (from QEMSCAN). Tomograms of carbonate cores and minicores were obtained with our in-house micro-CT scanners, which allow us a spatial resolution down to the order of 1 μm. Macroporosity, microporosity and pore networks were extracted by image processing and analysis using the MANGO software. These same cores and minicores were then sectioned for 2D maps of their mineral composition to be acquired by QEMSCAN and subsequently spatially registered into the corresponding 3D tomogram. In addition to this analysis of carbonate samples in their dry state, minicores were also prepared and micro-CT imaged in a series of wet states after saturation, drainage, aging and spontaneous imbibition. This facilitated visualization and quantification of the pore-scale changes in saturation during these processes. The observations will help to guide the further development of modelling and simulation of multiphase flow in carbonates to predict and enhance the recovery of oil.
Decision Analysis for Long-term and Short-term Production Optimization Applied to the Voador
Authors: Hasan Agus , Foss Bjarne , Krogstad Stein , Gunnerud Vidar , Teixeira Alex
Published: September 2013

Optimization of oil production may be performed on différent time horizons. Long-term optimization (which is typically performed over timescales of years) is usually conducted by reservoir engineers, whereas short-term optimization (which typically concerns days or weeks) is performed by production engineers. Long-term objectives focus on finding the best strategy to drain as much oil as possible from reservoirs. However, in reality it is often short-term goals such as maximizing daily oil rates that dictate the operational strategy. Unfortunately, these goals may be in conflict with each other. Therefore, incorporating long-term goals into short-term objectives is crucial. We present a novel approach to systematically combine long-term and short-term production optimization. The approach is based on a priori articulation of preferences, i.e., the decision maker is allowed to specify preferences that may be articulated in terms of goals or the relative importance of long-term and short-term objectives. The approach is adopted from multi-objective optimization method in which the solution is not a single point but rather a collection of points. To this end, we introduce the upper and lower bounds of the objective function such that the objective function can be written in a different form, whereas in reality, the short-term and long-term optimization are performed with the same objective but different methods. The idea is then to solve a bi-objective optimization problem using an adjoint-based method for the upper and lower objective functions and project the solution onto the original objective. The approach is tested on a simplified reservoir model of the south wing of the Voador field, which is located in the Campos Basin in Brazil. The results are presented as Pareto-like plots that can be used for decision support to balance long-term and short-term goals.
Reservoir Simulations of a Polymer Flood Pilot in the Pelican Lake Heavy Oil Field (Canada): a Step Forward
Authors: Delaplace P. , Renard G. , Delamaide E. , Euzen T. , Roggero F. , Kopecny P.
Published: September 2013

In 2005, a polymer flood was implemented at pilot scale in the six billion barrels OOIP, 800 to 80,000cp oil viscosity, Pelican Lake heavy oil field (Northern Alberta - Canada), to evaluate the potential of polymer to significantly increase the primary recovery limited to 5–7% OOIP. The pilot comprising 5 parallel horizontal wells (2 injectors and 3 producers) is still continuing in 2013 with excellent results (oil rate increase beyond expectations and surprisingly very slow water-cut increase in the 50–60% range) that have led the operator to extend polymer injection to field scale.

Understanding the wells responses to polymer flood, not totally expected in such a high viscosity oil, and optimizing the process have been undertaken through the following steps: 1) generation of a simplified reservoir model, consistent with geological trends and calibrated with core data, 2) automatic history matching of the pilot using dedicated tools, 3) investigation of sensitive parameters on oil recovery (well spacing, well length, polymer concentration, slug size, oil viscosity etc.), 4) range definition of optimum sensitive parameters both technically and economically.

Successful history matching of the pilot gives some insights on the main influence of reservoir heterogeneities on oil recovery. The history matched reservoir model has allowed to investigate the influence of various parameters for the implementation of polymer flood in heavy oil fields, and evaluate additional recovery compared to continued primary recovery or waterflood. It also provides some guidelines on the applicability of the process to other reservoirs.

History matching the pilot performance opens the door to a better understanding of polymer flooding in heavy oil reservoirs such as Pelican Lake and to increasing the number of potential application of polymer flood to similar fields.
Simulation Techniques for Surfactant Phase Behavior and Foam Flow Modeling in Fractured Reservoirs
Authors: Abbaszadeh Maghsood , Ren Guangwei
Published: September 2013

Simulations of foam-assisted surfactant chemical EOR in fractured systems require simultaneous modeling of foam flow in fractures for mobility control and chemical EOR in matrix by diverted surfactant solution. Modeling of surfactant phase behavior as a function of salinity and representing microemulsion (ME) properties are challenging because commercial simulators lack the capability to explicitly model these complex chemical processes. In this paper, we develop and validate techniques for simultaneous modeling of foam flow and surfactant-oil-brine key characteristics, using the general framework of CMG-STARS commercial simulator. Laboratory surfactant-salinity phase behavior data is transferred into k-value based compositional model, where oil is also characterized by multi-components. Surfactant Winsor Type phase variations are tracked by a pseudocomponent based on combined surfactant-salinity criteria, an invention of this paper. The mobility control provided by foam is fulfilled by bubble model of low quality liquid foam with increased aqueous phase viscosity through bubble characteristics.

2D cross section models are constructed for the modeling of foam transport in fractures and surfactant EOR processes in matrix. The critical process physics of surfactant phase behavior is represented in detail, including k-value based component splitting between phases, viscosity variation of ME phases and the corresponding interfacial tension reduction. The results show that our developed methodologies correctly account for diversion of surfactant solution into matrix for intended chemical EOR processes and for mobility control by foam flow in the fractures. Investigation of phase viscosities, IFT and compositions show that the modeling of ME phases and representing their properties in various gridblocks of the simulation model and over different time intervals follow the underlying process mechanism. As such, the techniques developed provide a methodology for modeling foam-surfactant chemical EOR in naturally fractured reservoirs within the framework of available commercial simulators and along with their limited functionalities.
Using Near Wellbore Upscaling to Improve Reservoir Characterization and Simulation in Highly Heterogeneous Carbonate Reservoirs
Authors: Chandra V. , Geiger S. , Corbett P. W. , Steele R. , Milroy P. , Barnett A. , Wright P. , Jain P.
Published: September 2013

Carbonate reservoirs host a major portion of the world's remaining conventional and unconventional hydrocarbon reserves, typically containing multi-scale geological heterogeneities varying over many orders of magnitude in size. Characterizing and representing them robustly in reservoir models is a prime challenge in carbonate reservoir simulation. One of the key aims of this paper is, hence, to present a novel near wellbore upscaling (NWU) workflow that addresses the challenges associated with conventional carbonate modelling workflows. The NWU workflow provides a systematic geostatistical approach to obtain more realistic representation of multi-scale geological-petrophysical heterogeneities in complex carbonate reservoir simulation models. Using well log and core data, near wellbore regions were recreated to represent the core scale heterogeneities via high resolution geostatistical models. These core/centimeter scale permeability models were then upscaled into wireline/decametre scale using flow-based upscaling. The results, coupled with wireline data were used to generate global porosity-permeability and vertical-horizontal permeability relationships for reservoir simulation. Importantly, the workflow mitigates sample bias, which is frequently observed in the core data for carbonate reservoirs. We have applied our approach to a mature carbonate field, to model and upscale crucial multi-scale heterogeneities ubiquitous in the reservoir. These heterogeneities, such as mechanically weak zones of enhanced micro- and macro-porosity, leached stylolites and associated tension gashes, were caused by diagenetic corrosion. Core plugs representivity is always an issue in carbonates and these highly corroded features were very difficult, if not impossible, to sample due to their fragility. As a result, the field suffers from inherent sample biasing and insufficiency of Routine Core Analysis (RCA) data, consequently underestimating the permeability in the simulation model. The workflow presented here has enabled the authors to re-evaluate the reservoir permeability model by accounting for as yet under-sampled geological heterogeneities. The paper represents a focused individual study addressing this specific issue and doesn't necessarily reflect the operator's full understanding of this multifaceted field. Our new permeability model has addressed the need for artificial permeability multipliers and provided insight on the potential causes of the original mismatch. As a result, a new alternative model scenario has been built to help guide the on-going development plans and forecasting incremental oil recovery.
Insight into Smart-Water Recovery Mechanism through Detailed History Matching of Coreflood Experiments
Authors: AlSofi Abdulkareem M. , Yousef Ali A.
Published: September 2013

A practical Smart-Water flooding simulation model should replicate laboratory and pilot scale observations. An ideal model, however, should also capture the recovery mechanism in play. In the literature, only the conventional straight forward residual oil reduction approach has been suggested and tested to upscale Smart-Water Flood laboratory results. This, consequently, provides a single view of the potential recovery mechanism. Other approaches can be equally successful in matching laboratory results and hence could provide additional insight and understanding of the recovery mechanism in play. In this work, we use the laboratory results of two tertiary Smart-Water corefloods to investigate the various possibilities for modeling Smart-Water flooding—hence, the possible recovery mechanisms.

First, we use a high-accuracy Buckley Leveret solver to study the performance of the two corefloods from a fractional flow perspective. Second, we use a streamline-based simulator to investigate in detail the possible relative permeability sets capable of history matching Smart-Water recoveries and pressures. As a result a new set of relative permeability was generated, and tested through a 3-D synthetic layered reservoir to demonstrate Smart-Water flooding recoveries. The results of this work suggest that recovery enhancement through Smart-Water flooding is best explained based on changes to the curvature of the oil relative permeability curve (i.e. the Corey oil exponent). Incremental recoveries are realized not due to a reduction in the "technical/absolute" residual oil but rather due to improvement in the oil flow capacity (i.e. oil-to-water relative permeability ratio). Based on our results, we postulate that Smart-Water incremental recovery is triggered by the formation of a dual wettability state across the porous medium.
Minimization of Disparity between Well test and Log Driven Permeabilities through Combination of Rock-physics And Advanced Logs with Proper Averaging Technique
Authors: Vorobiev Sergey , Altunbay Michael M. , Vorobyev Vladimir , Overseas Lukoil , Johari Azlan Shah
Published: September 2013

Minimization of disparities between welltest and log-derived average permeabilities has always been an issue, particularly in carbonates where complex pore structures add on challenges to permeability estimation from wireline log data. The disagreement between permeability averages from logs and well tests originates from the combined effects of measurement-scale of static porosity components for permeability models, dual flow system of fractures and matrix, tensorial nature of permeability and the averaging techniques used.

The proposed workflow exploits rock-physics templates to identify and to quantify secondary porosity. Rock-physics templates employ conventionally derived total porosity and shear modulus as inputs. Fracture and vug porosity identified by the proposed workflow through rock-physics agree with other qualitative and quantitative evidences of non-primary porosity obtained from NMR, Image logs and core data1. Matrix and connected-vug permeabilities are computed, calibrated and integrated via "Chen-Jacobi" connectivity-driven model2 by using NMR and acoustic log data. Fracture permeability is estimated from "fracture aperture" and fracture-porosity by using image log data and rock-physics algorithms. The final permeability profile is computed with a selective-replacement step. This step ensures that in co-presence of matrix, connected vugs and fracture permeabilities at a given discrete depth level, the greater one would dominate and replace the lesser one. The final step in efforts of lessening the disparity between averages of wireline-driven and well test/DST permeabilities for a given interval is the usage of proposed averaging technique for the integrated wireline-driven permeability profile.

The rock-physics templates used in this study combine Kuster and Toksoz3 "inclusions" theory with the Dvorkin-Nur4 granular media model (1996). We have observed appreciable correlations between secondary porosity driven from shear velocities against the secondary porosity determined from NMR and Image logs and core data. These correlations further provide routes for newer permeability models that can be solely based on the rock-physics.

Comparisons of permeability averages computed from wireline-driven permeability profiles against DST or welltest permeability showed significant improvements toward parity via proposed methodology and averaging technique. The workflow presented in this study is to guide the reader through numerous steps of the proposed algorithm in detail.
Evaluating Possible Solutions to Enhancing Injectivity in Low Permeability Reservoirs - A Modeling Perspective
Authors: Akuanyionwu Obinna , Stigliani Roberto Buonamassa , Norris Mark , Richardson Benjamin
Published: September 2013

The ability to achieve and sustain injectivity has a fundamental and significant bearing on the success or failure of a water injection project. Restricted and/or impaired injectivity can result from a number of factors ranging from poor reservoir quality to process-induced formation damage issues among others. For the case of poor reservoir quality, a solution may lie in adapting wellbore configurations to maximize reservoir contact. However, applying these solutions demands an extensive prior evaluation of risk-weighted benefits of available technology options, including implications under varying degrees of uncertainty.

This paper compares multilateral and hydraulically fractured well technologies as means to enhance injectivity in low permeability reservoirs. A conceptual approach – from a simplified homogenous model to a more detailed heterogeneous model - is employed. A reference high angle injector well type is selected, and an injectivity improvement factor calculated for different multilateral and fractured well options. Several sensitivities were also performed to assess the exposure of selected wellbore configurations to subsurface uncertainties. The evaluations were also extended to naturally fractured syste m sensitivities.

We find that as reservoir quality deteriorates, the benefit in injectivity improvement becomes even more accentuated with carefully selected wellbore configurations. Additionally, the need for proper considerations for well placement is highlighted. Finally, the work underlines some broad guidelines supporting discussions on meeting of water injection and reservoir management objectives in similar reservoirs.
Application of Integrated Asset Modeling Approach in a Multi-Reservoir Gas Condensate Field
Authors: Rahmouni Noureddine , Al-Shabibi Tariq Ali , Al Khanbashi Salem , Amtereg Ahmed , Bouaouaja Mohamed , Soendoro Feddy Himawan
Published: September 2013

This paper presents an application of integrated asset modeling (IAM) to a rich gas condensate field under recycling mode located in Abu Dhabi. The field is composed of many non communicating gas reservoir units; some of these units are already developed and being produced for a number of years, while some others reservoirs are in the exploration / evaluation phase. Potentially, some of the reservoir units are sharing or will share the surface network and the process facilities. The project consists of developing a platform for a solution that can respond to the current requirement of the available modeled reservoirs; at the same time, the solution should be expandable to account for the reservoirs being explored or at early production phase.

The first step of the study was to construct the surface network for both gas injectors and gas producers. The subsurface compositional simulation models for the developed reservoirs were available and history matched. The platform linking the surface to subsurface was developed and set to fulfill the field development requirements. The solution was validated for the historical performances, measurement of the surface network were collected and validated in the stand-alone mode and in the coupling mode. Tests for the prediction performances were also performed, and led to more realistic profile showing the recoverable reserves for recycling and blowdown considered scenarios.

The integrated model indicated area of improvement in pressure history match of the field simulation model for few wells where it was not easy to observe in standalone simulations.

The platform for the integrated Asset modeling is expandable to further development that could be plugged-in, either functional adds-on like process modeling and economic evaluation or organic like adding additional wells to the existing models or adding new models for exploration unit. It will be also applicable to see the compression requirements during any time in the future.
Stacked Reservoirs Development Optimization Based on a Fully Implicit Surface-Subsurface Nexus Modelling - A Case Study from the UAE
Authors: Clara Cédric , Sherief Mohamed , Chong Tee Sin , Abdou Medhat
Published: September 2013

The efficient development of Abu Dhabi's giant stacked reservoirs is challenging due to the significant number of wells needed to produce these reservoirs through common surface production facilities. Historically the development planning was carried out based on individual, single reservoir, numerical simulation models that have been managed by applying independent boundary conditions such as rate and pressure constraints. With time this solution became inefficient due to other considerations such as production facilities size and cost, surface congestion affecting the area available to drill wells and lay down transfer lines, drilling and rigless operations.

Recent advances in numerical simulation, such as the simultaneous implicit solution of pressure and other properties in an asset model which includes both surface facilities and the subsurface reservoir, provide users with the ability to understand the flow of oil from the pore space of the reservoir through the surface network to the ultimate point of sale. The Nexus® simulator extends this capability to multiple reservoirs with a shared surface network, while keeping the implicit solution throughout the entire multi-reservoir complex. Reservoir engineers can now build field development plans based upon the results of simulations which address the entire complex, rather than assembling the results of separate simulations of individual fields and independent network models. Modelling the integrated asset allows the engineer to synchronize well phasing and planning, optimize production rates, and maximize surface facility utilization.

This case study discusses an ADCO onshore field development plan combining several stacked reservoirs within a sequence of 18 stacked, independent reservoirs in the same field. All developed reservoirs within the sequence share common surface facilities. The integrated model construction is presented including gridding, fluid properties, surface network configuration and constraints. The economic value of different production and injection scenarios and their impact on shared facilities is also discussed which led to optimizing the well phasing, plateau rate and length of the combined developments.
Narrowing the Loop for Microporosity Quantification in Carbonate Reservoirs
Authors: Al Ratrout A. A. , Kalam M. Z. , Gomes J. S. , Jouini M. S.
Published: September 2013

Microporosity quantification is becoming increasingly important to assess the distribution of hydrocarbons and their remaining/residual saturations after water flood (and /or gas flood). Assessing uncertainties and limitations in microporosity estimations of carbonate cores, comprising different reservoir rock types have been a challenge for geoscientists. The advent of Digital Rock Physics (DRP) based measurements allow the pore 3D network images from Micro and Nano - Computed Tomography (CT) scans on selected sub-samples to map representative cores and Reservoir Rock Types (RRT). The DRP based microporosity is rigorously examined and compared with other techniques/tests. Conventional techniques, such as Mercury Injection Capillary Pressure (MICP), Nuclear Magnetic Resonance (NMR), Thin Section (TS) and Backscattered Scanning Electron Microscopy (BSEM) are used for semi-quantitative evaluations of microporosity. Images at different magnitudes (4X, 10X, 40X and 100X) were captured from TS and BSEM, and used to quantify porosity using image analysis software. NMR and MICP measurements acquired through a commercial laboratory were also analyzed to quantify the microporosity. DRP based 3D pore network images have been acquired at different scales of interrogation from Nano to micron meters to define microporosity. Preliminary measurements on carbonate cores from a giant onshore field of Abu Dhabi, reveals an inverse relationship between microporosity and permeability.

Microporosity impacts the porosity-permeability correlation. The relationship between porosity and permeability of carbonate reservoirs shows a better correlation when microporosity is deducted from the total porosity of the reservoir. A detailed analysis is presented along with Best Practices in estimating microporosity of carbonates.
When a Good History-Matched Model Results in a Bad Forecast; Question your Petrophysical Data
Authors: Qutob Hani H. , Khlaifat Abdelaziz , Efnik Mohamed S.
Published: September 2013

When implementing any field development plan or an Enhanced Oil Recovery (EOR) project, it is critical to understand the key variables that influence the success of the plan such as; reservoir parameters and fluid properties. Mature Oil & Gas fields' increasing complexity of recovery mechanisms dictates an improved understanding of the fields' behaviour and the technologies that must be applied to maintain and prolong oil production plateau and achieve ultimate recovery potential.

History matching forms an integral part of the reservoir modeling workflow process. It is used to examine the field performance under different production and injection scenarios in order to select the best scenario for hydrocarbon production. However, the history-matching process can be very frustrating and time-consuming, even for fields that appear relatively small and simple in nature, because of the reservoir processes involved and the non-unique nature of the solution.

Traditionally, history matching is conducted as a deterministic process with a single realization considered representative at a single point in time. Although, the input data usually go through a data analysis process where the major uncertainties and scenarios are defined, and uncertainty ranges are created, time and budget constraints usually result in significant reductions in the number of sensitivity runs and analysis for the input data validation and quality control that results in an incomplete investigation of the uncertainty quantification. Therefore, uncertainties inherited in the Petrophysical data are carried from the static model construction throughout the entire dynamic modelling process, ultimately leading to less-than-optimal models to be used as a decision making tool.

Consequently, due to the non-uniqueness of the numerical solution, a good history-matched model might have geological and petrophysical properties quite far from those of the "Field" and therefore could lead to a bad forecast. As in any numerical model, petrophysical data quality is fundamental for model precision.
Revealing Relative Permeability Uncertainties through Integrated Experimental and Modeling Workflow
Authors: Yaslam Maged , Ghedan Shawket G. , Kalam Zubair
Published: September 2013

Relative permeability profile is one of the most uncertain parameters and challenging requirements in field performance models. It is a mandatory element for multi-phase flow calculations and has a significant impact on development schemes, expected hydrocarbon recovery factor and the related revenues. Moreover, it impacts the surface facilities decision based on predicted produced fluids and recycling requirements, which might affect the economics of any related projects. Accordingly, obtaining representative relative permeability profile is a historical continuous challenge in the industry through common laboratory methods of steady state and unsteady state along with other numerical modeling approaches.

Experimental relative permeability profiles using both methods of steady state and unsteady state have been obtained for one of the main reservoir rock types (RRT A) from a giant carbonate field in the Middle East. Comprehensive characterization and detailed numerical modeling for mixed wettability carbonates at full reservoir conditions has been studied covering all the details of rock properties, capillary pressure coupled with relative permeability profiles. The analysis revealed the uncertainty associated with each measurement method and surprisingly the limited data range of unsteady state method. Moreover, for the selected reservoir rock types, non-unique relative permeability profiles have been obtained using various experimental approaches and empirical correlations within the numerical modeling process in which different produced relative permeability profiles matched reasonably the laboratory reference measurements.

The resultant relative permeability profiles associated with uncertainty range presented in this paper has shown the significant influence of the measurement method selection, which impact the dynamic simulation models predictions and the eventually field development options. This work provides insight on experimental methods selection and optimum conditions to acquire representative relative permeability profiles with emphasis on possible sources of uncertainties and errors. It clearly demonstrates the relative permeability accuracy levels of various numerical modeling processes and the potential of non-unique profiles which dictate the reservoir dynamics, performance as well as economics.
Use of Digital Imaging for Improved Evaluation of Unconventional Reservoirs
Authors: Dixon Michael , Newton Barry , Schwartz Angela , Smart Erin , Hooghan Kultaransingh (Bobby)
Published: September 2013

Formation evaluation of rock material from unconventional reservoirs is challenging due to the rock's typically heterogeneous nature and low permeability. Measurements and descriptions of the pore network in shale/mudstone are especially difficult due to variations in mineralogy, texture and pore size. In the digital rock domain, high resolution imaging of core can be obtained from the meter to nanometer size range to create respective 3D models. Data obtained with these techniques can be integrated with other core analysis data (i.e. geochemistry, petrology, mechanical properties) to provide expanded modeling capabilities for integrated core studies of unconventional reservoirs.

This paper describes how an integrated imaging/sampling protocol serves to characterize unconventional reservoirs across a broad size range. High resolution digital imaging data derived from Helical Computed Tomography (HCT) and micro-CT captures meter- to millimeter-sized features, while Field Emission Scanning Electron Microscopy (FE-SEM), and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) provide the means to characterize the rock fabric and pore network on a sub-micron (<nm) level. For this study, a 4-inch diameter core from a proprietary well in the Middle East was submitted to Weatherford Laboratories in Houston, Texas, for analysis.

Sections of core were first imaged/analyzed using HCT. Based on observations from HCT images, samples were subsequently selected for micro-CT, FE-SEM, and FIB-SEM. Though the HCT images were also used to select data points for traditional core analysis (i.e. thin section petrography, X-ray diffraction, geochemistry, etc.), those data sets will be presented at a later date, and the focus of this paper is the use of digital imaging to characterize selected samples. The resulting images and accompanying data sets acquired in this study illustrate how digital imaging methodologies can be used to characterize the controls on reservoir quality (including depositional fabrics, structural relatioinships, diagenetic relationships, and the pore network), and ultimately lead to a better understanding of well performance in unconventional reservoirs.
Local effects of global climate change on the urban drainage system of Hamburg
Authors: Krieger Klaus , Kuchenbecker Andreas , Hüffmeyer Nina , Verworn Hans-Reinhard
Published: September 2013

The Hamburg Water Group owns and operates a sewer network with a total length of more than 5,700 km. There has been increasing attention paid to the possible impacts of predicted changes in precipitation patterns on the sewer network infrastructure. The primary objective of the work presented in this paper is an estimation of the hydraulic impacts of climate change on the Hamburg drainage system. As a first step, simulated rainfalls based on the regional climate model REMO were compared and validated with long-term precipitation measurements. In the second step, the hydraulic effects on the sewer network of Hamburg have been analyzed based on simulated long-term rainfall series for the period of 2000–2100. Simulation results show a significant increase in combined sewer overflows by 50% as well as an increase in surcharges of storm sewer manholes. However, there is still a substantial amount of uncertainty resulting from model uncertainty and unknown development of future greenhouse gas emissions. So far, there seems to be no sound basis for the implementation of an overall climate factor for sewer dimensioning for the Hamburg region. Nevertheless, possible effects of climate change should be taken into account within the planning process for major sewer extensions or modifications.
Effective growth of dinoflagellate Prorocentrum minimum by cultivating the cells using municipal wastewater as nutrient source
Authors: Ho Kin-Chung , Xu Steven Jing-Liang , Wu Kam-Chau , Lee Fred Wang-Fat
Published: September 2013

Several studies have been conducted worldwide in order to develop a more economical method for mass algal cultivation so that more cost-effective biomass production can be accessed. One of the directions is to reduce production costs by using wastewater as a nutrient source in algal cell cultivation. The growth ability of a red-tide causative dinoflagellate species, Prorocentrum minimum, in various concentrations of local urban wastewater was examined in this study. The highest exponential growth rate and maximum cell density (MCD) were achieved when autoclaved 10% wastewater was used for cell cultivation, although the cells could survive in 0.01–100% wastewater. Both growth rate and MCD of the cells in wastewater were found to be substantially higher than that in optimized L1 culture medium. This research highlights the potential of using wastewater as a cost-effective approach for mass cultivation of dinoflagellate cells with consequent production of valuable microalgal biomass.