bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.