bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research Progress and Applications of the Joint Industry Programme on Exploration and Production Sound and Marine Life
Authors: Weissenberger Jürgen , Campbell John , Notor Lori , Hedgeland David , Jenkerson Mike , Melton Rodger , Rea Caryn L. , Tait Russell D. , Tsoflias Sarah L. , Brookes Chisa K. , Michael Jennifer Liebeler 
Published: February 2011

Abstract
The international oil and gas industry recognizes there is increased interest by multiple stakeholder groups on the effects of anthropogenic sound in the marine environment. This interest is focused on, but not limited to seismic surveying. While little to no scientific evidence exist associating seismic surveys with significant adverse impacts on marine animal populations, gaps in knowledge increase the uncertainty in identifying key risks that can be adequately mitigated.
Consequently, the regulatory community often imposes very precautions and often impracticable restrictions on seismic surveys to prevent or mitigate perceived impacts. With the implementation of such restrictions, the cost of data acquisition can ultimately triple with no more than an incremental benefit to the receiving environment. To this end, the Joint Industry Program on Sound and Marine Life (JIP) has implemented a robust research and monitoring program to compile and/or acquire scientific information to fill gaps in knowledge concerning the impacts of anthropogenic sound on marine life. The projects, conducted by independent research entities, are focused on three key areas: 1) inventory the various sounds introduced to the water by the oil and gas industry (source); 2) understand the propagation of sound in the marine environment (pathway); and 3) identify any potential physical or physiological impacts on marine life (receiver).
The JIP has funded approximately 70 research projects with the overarching goal of understanding the environmental risks (exposure and consequences or effects) associated with offshore Exploration and Production (E&P) operations. Improved scientific knowledge surrounding the consequences of exposure to sound will help inform risk assessments conducted by industry project teams, as well as inform the scientific community and regulators about the potential environmental effects of these operations. The availability of these project data should result in permit decisions by regulators that are supported by sound science with appropriate mitigation and monitoring procedures. Examples of representative projects being sponsored by the JIP are described in this paper.
Updated information on the progress of the JIP founded research can be found at www.soundandmarinelife.org
HVAC as Major Safety Parameter in Arctic Environment
Authors: Dalheim J.. , Nodland S.. 
Published: February 2011

Abstract
The harsh environment of the arctic requires specialized safety solutions. One main safety issue in the arctic is the need for more enclosed modules. Enclosed modules are used for two reasons; to prevent: process equipment from ice and snow exposure; the cold climate imposing an unduly harsh working environment for operators. The enclosed mechanically ventilated process modules are different from the open naturally ventilated process modules that are normally used in offshore facilities. The explosion safety performance of the non-standard mechanically ventilated process modules has therefore been studied in detail through an extensive program of CFD simulations. It is seen that mechanically ventilated modules have explosion risk drivers that are distinctly different from risk drivers in naturally ventilated modules. Several unique factors are seen to have significant impact on the explosion risk levels of confined process modules; the module size; the HVAC philosophy; the ignition source isolation efficiency; and the use of pressure relief panels. This paper discusses one of the main explosion safety drivers for mechanically ventilated modules; the HVAC system. The presented conclusions are of great importance for future development in the arctic climatic environment.
Gas-Lift Optimization Using Proxy Functions in Reservoir Simulation
Authors: Lu Qin , Fleming Graham C. 
Published: February 2011

Abstract
Artificial lift by means of gas injection into production wells or risers is frequently used to increase hydrocarbon production, especially when reservoir pressure declines. We propose an efficient optimization scheme that finds the optimal distribution of the available gas-lift gas to maximize a benefit function subject to surface pipeline network rate and pressure constraints. This procedure is formulated as a nonlinearly constrained optimization problem solved by the Generalized Reduced Gradient (GRG) method. The values of benefit function, constraint functions, and derivatives needed for optimization can be evaluated through two methods. The first method repeatedly solves the full-network equations using Newton iteration, which takes into account the flow interactions among wells; however, this method can be computationally expensive. The second, and more efficient, method constructs a set of proxy functions that approximates the benefit function and constraints as functions of gas-lift rates. They are obtained by solving part of the network that consists of a gas-lifted well or riser, assuming a stable pressure at the terminal node where the partial network is decoupled from the rest of the network, and are used to inexpensively evaluate the benefit function, constraints, and necessary derivatives for the optimizer. A procedure to predict the proxy functions based on previous values can be used to reduce the number of partial network solves, and the partial network solution has been parallelized for faster simulation. The proposed methods are implemented within a generalpurpose black-oil and compositional reservoir simulator and have been applied to real-field cases.
An Advanced Framework for Simulating Connected Reservoirs, Wells and Production Facilities
Authors: Hiebert Allan , Khoshkbarchi Mohammad , Sammon Peter , Alves Ibere , Rodrigues Jose Roberto , Belien Alexander , Howell Benjamin , Saaf Fredrik , Valvatne Per 
Published: February 2011

Abstract
The ability to accurately simulate and optimize fully integrated oil and gas fields is of critical importance in the development and operation of an asset. To this end, a novel and comprehensive framework for simulating fields comprised of connected reservoirs, wells, and production facilities is presented. Individual field components may be connected to each other through physical equipment such as pipes, and operations may be subject to field-wide constraints, such as limits on total production of green house gases. The proposed framework allows for simulation of the evolution of such a field, optimization of the field under various constraint choices, and planning and scheduling of the entire field operations. The framework is founded on representing each component using appropriate sets of Models, Equations and Variables (MEV) combined with a common Physical Property Manager that ensures a consistent calculation methodology, and uses grid-level partitioning to support parallelism. The MEV system operates in concert with customized nonlinear and linear equation solvers to generate updated values for variables in all the different sub-systems, regardless of their originating component. Optimizers in the system manipulate the same variables employed in the MEV solution process to assemble objective functions, act on decision variables, and satisfy constraints. These variables may also be parameterized to support uncertainty analysis or design possibilities. The componentized nature of the equation set allows the ability to plug in alternate custom technologies to replace or augment capabilities. The framework supports multiple fidelities for modelling the components, and enables the use of different coupling styles between them. Choices range from using simple proxy models for certain components, to explicit one- and two-way coupling of more rigorous models, up to solving a fully coupled, detailed field representation. It will be demonstrated that this approach allows for efficient simulation of the combined systems under different constraints.
Near-Well Subdomain Simulations for Accurate Inflow Performance Relationship Calculation to Improve Stabil ity of Reservoir-Network Coupling
Authors: Guyaguler B. , Zapata V. J. , Cao H. , Stamati H. F. , Holmes J. A. 
Published: February 2011

Abstract
Externally coupled workflows that rely on exchanging Inflow Performance Relationships (IPRs) at the coupling points, such as those between reservoir and surface network simulators, may exhibit instabilities due to the fact that the IPR calculated at the beginning of a timestep is not representative of the IPR at the end of the timestep. One solution is to have an implicitly coupled reservoir-surface system. This is often impractical because reservoir and surface networks are modeled using different applications, but also in cases where the resulting coupled system becomes too large and complex to solve implicitly due to processing time and convergence issues. We propose the calculation of multipoint, nonlinear IPRs by solving near-well subdomains for the subsequent timestep. A flexible reservoir simulation architecture enables the dynamic creation and simulation of near-well subdomains at run time. Subdomains are automatically created within the vicinity of the well, or defined dynamically from the pressure gradient. These near-well subdomain simulations are embedded within the full-field simulation, and extract all the required model properties (PVT, rock, etc.) from the full-field model. The most recent fluxes from the global solution are used as boundary conditions of the near-well subdomains. The IPRs created through subdomain solutions agree with those generated by carrying out the full-field simulation multiple times. In this paper, the subdomain IPRs are used within reservoir-network coupling workflows in which regular IPRs result in oscillations and high errors. Sensitivity analysis is carried out on the extent of the subdomains and the size of the coupling timestep. It is shown on a real field case that the subdomain IPRs result in stable coupling for the otherwise unstable model and also help in reducing the balancing errors.
History Matchinga Field Case Using the Ensemble Kalman Filter with Covariance Localization
Authors: Emerick Alexandre A. , Reynolds Albert C. 
Published: February 2011

Abstract
Because of its ease of implementation, computational efficiency and the fact that it generates multiple history-matched models, which conceptually allows one to characterize the uncertainty in reservoir description and future performance predictions, the ensemble Kalman filter (EnKF) provides a highly attractive technique for history matching production data. In this work, we apply EnKF with a recently proposed method of covariance localization to history-match production data from a real field to generate multiple realizations of the permeability field. A single manually history-matched model is available for comparisons. Only 7.6 years of the 10 years of history were matched with the remaining 2.4 years of history used to assess the predictive capability of the history-matched models. For this field case, covariance localization was necessary to avoid the propagation of spurious correlations and loss of variance and also resulted in better data matches and predictions than were obtained with EnKF without localization. EnKF with covariance localization also gave better data matches, more accurate "future" predictions and far more geologically realistic models than were obtained by manually matching production data. We also present results obtained using half-iteration EnKF (HI-EnKF) with covariance localization. For this field case, HI-EnKF gave a significant further improvement in the data match and predictions. However, as HI-EnKF requires rerunning the ensemble from time zero at every data assimilation step, it leads to a considerable increase in the computational time. The results for this field case indicate that we can reduce the computational cost of HI-EnKF, without compromising the quality of the results, by rerunning the ensemble from time zero only when "large" changes in the state vector occur.
Rigorous Coupling of Geomechanics and Multiphase Flow with Strong Capillarity
Authors: Kim J. , Tchelepi H. A. , Juanes R. 
Published: February 2011

Abstract
The average pore-pressure, p¯, defined as the sum of the product of the saturation and pressure of the fluid phases is widely used as the average pore-pressure of multiphase fluid systems in deformable porous media. Using the incremental formulation, Coussy (2004) shows that for systems with multiple fluid phases, the ‘equivalent’ pore-pressure, pE, defined as p¯ minus the interfacial energy is the appropriate quantity. We investigate the accuracy and stability of the fully implicit method (FIM) for multiphase flow and mechanical deformation based on p¯ and pE. We then study the convergence and stability properties of sequential-implicit coupling strategies. The findings from stability theory are verified using nonlinear simulation of two-phase flow with mechanical deformation. Our analysis of FIM for systems with strong capillarity indicates that using p¯ leads to serious numerical instabilities, and to significant deviations from the reference solution even when the solutions are stable. Our analysis and simulation results indicate that, in contrast, using pE leads to unconditional stability and accurate solutions.
For the sequential-implicit coupling strategies, our previously published results for single-phase flow carry over for multiphase systems when the equivalent pore-pressure, pE, is used in the conservation equations and constitutive relations. Specifically, the undrained and fixed-stress schemes are unconditionally stable. The fixed-stress split is superior to the undrained approach in terms of convergence behavior. Therefore, we recommend the incremental formulation based on the equivalent pore-pressure for coupled multiphase flow and mechanics. In terms of stability and convergence properties, we recommend the fixed-stress sequential-implicit scheme.
Maximization of a Dynamic Quadratic Interpolation Model for Production Optimization
Authors: Zhao Hui , Chen Chaohui , Do Sy , Li Gaoming , Reynolds Albert C. 
Published: February 2011

Abstract
We derive and implement a new optimization algorithm based on a quadratic interpolation model (QIM) for the maximization (or minimization) of a cost or objective function. Although we have also applied the algorithm in other petroleum engineering applications, this paper restricts the algorithm's application to the production optimization step of closed-loop reservoir management where the objective function is the net present value (NPV) of production from a given reservoir. The new algorithm does not require a gradient calculation with an adjoint method but does use an approximate gradient (AG). Thus, the general optimization algorithm is referred to as QIM-AG. At each iteration, the QIM-AG algorithm builds a quadratic model which approximates the objective function using the approximate gradient and interpolation points. As the number of interpolation points is usually far less than the number of coefficients in the quadratic model, the extra degrees of freedom are used to minimize the Frobenius norm of the Hessian matrix of the quadratic model. The quadratic model is then maximized using a trust-region method. As more objective function evaluations become available during iteration, the quadratic model is updated with new interpolation points and an approximate gradient. The performance of the new algorithm is compared with the performance of several algorithms which are either derivative-free or use only a derivative approximation which can be calculated without using the adjoint method. The derivative-free optimization algorithms considered for comparison include NEWUOA (New Unconstrained Optimization Algorithm), SID-PSM (Pattern Search Method guided by Simplex Derivatives), PSO (Particle Swarm Optimization), EnOpt (ensemble-based optimization) and SPSA. A brief conceptual summary of these other derivative-free algorithms is given and it is shown that the approximate gradient implicitly used in EnOpt can be directly related to the simplex gradient used in SID-PSM.
For a set of three distinct examples, the QIM-AG algorithm generally outperforms the other derivative-free optimization algorithms. Specifically, QIM-AG obtains an estimate of optimal controls that gives the highest NPV in two of the three examples and within 0.1% of the highest value in the third example.
Multi-level Parallelization of Ensemble Kalman Filter for Reservoir History Matching
Authors: Tavakoli Reza , Pencheva Gergina , Wheeler Mary F. 
Published: February 2011

Abstract
The ensemble Kalman filter (EnKF) has been successfully implemented to assimilate data in reservoir history matching problems. In the EnKF method, a suite of reservoir models (set of ensemble members) runs independently forward in time (forecast step), and is continuously updated as new data becomes available (analysis step). In this paper, an efficient implementation of the EnKF is presented in which three-level parallelization is employed.
The first level of parallelization is during the forecast step, where each ensemble member runs on a separate processor. This is very efficient for a large number of ensemble members, but without additional parallelization, the memory of a single processor constrains the size of the reservoir simulation. Therefore, a second level of parallelization which uses a parallel reservoir simulator for each realization is implemented. The analysis step requires collecting a state vector from each ensemble member. If this data is collected on a single processor, this poses an additional limitation on the size of the EnKF problem in terms of both memory and computation time. Therefore, we propose an algorithm in which a third level of parallelization is achieved for the analysis step. The main computational gain of parallelization of the analysis step comes from the fact that the matrix-vector multiplications can be parallelized efficiently.
The parallel EnKF algorithm is applied to a set of reservoir history matching problems. The effect of ensemble sizes on the history matching results is investigated. We present computational results that show the efficiency is greatly enhanced by moving from a serial to a parallel implementation of the EnKF. The initial testing of parallel EnKF has been done on the massively parallel machines Ranger and Lonestar, at the Texas Advanced Computing Center (TACC), and the cluster Bevo2, at the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin.
Uncertainty Quantification in History Matching of Channelized Reservoirs using Markov Chain Level Set Approaches
Authors: Xie Jiang , Efendiev Yalchin , Datta-Gupta Akhil 
Published: February 2011

Abstract
We present a method for history matching and uncertainty quantification for channelized reservoir models using Level Set Method and Markov Chain Monte Carlo. Our objective is to efficiently sample realizations of the channelized permeability fields conditioned to the production data and facies observation at the wells. In our approach, the channel field boundary is first described by a level set function, e.g., a signed distance function or any other indicator function. By solving the level set equation (motion in a prescribed direction), we are able to gradually move the channel boundaries and evolve the channelized reservoir properties. Our approach allows representing facies via a parameterization of the velocity field that deforms the interface. Thus facies can be parameterized in the space of smooth velocity fields. The dimension reduction can be achieved for covariance-based velocity fields by re-parameterizing with SVD techniques.
After parameterization, Markov Chain Monte Carlo method is utilized to perturb the coefficients of principal components of velocity field to update channel reservoir model matching production history. One advantage of this approach is that it is easy to condition the channel model to the facies observations at well locations by constraining the random velocity field to zero at well locations. To speed up the computation and improve the acceptance rate of the MCMC algorithm, we employ two stage methods where coarse-scale simulations are used to screen out the undesired proposals. The MCMC algorithms naturally provide multiple realizations of the permeability field conditioned to well and production data and thus, allow for uncertainty assessment in the forecasting. We demonstrate the effectiveness of the level set MCMC algorithm using both 2D and 3D examples involving waterflood history matching.
A Negative-Flash Tie-Simplex Approach for Multiphase Reservoir Simulation
Authors: Iranshahr Alireza , Voskov Denis , Tchelepi Hamdi A. 
Published: February 2011

Abstract
Enhanced Oil Recovery (EOR) processes usually involve complex phase behaviors between the injected fluid (e.g., steam, hydrocarbon, CO2, sour) and the in-situ rock-fluid system. Several fundamental questions remain regarding equation-of-state computations for mixtures than can form three, or more, phases at equilibrium. In addition, numerical and computational issues related to proper coupling of the thermodynamic phase-behavior with multi-component transport must be resolved in order to model the behaviors of large-scale EOR processes accurately and efficiently.
We describe a general negative-flash method for multi-component, thermal systems that can form three, or more, fluid phases. We prove that the new method is convergent to the unique solution. This negative-flash approach is integrated with reservoir flow simulation based on adaptive tie-simplex parameterization of the compositional space. We prove that the tie-simplexes change continuously as a function of pressure, temperature, and composition. The continuity of the parameterized space allows for interpolation in pressure and temperature using a limited number of tie-simplexes. This extended negative-flash approach accounts rigorously for tie-simplex degeneration across phase boundaries.
We study the behaviors of thermal-compositional reservoir displacement processes across a wide range of fluid mixtures, pressures, and temperatures. The focus is on the complex behaviors of the tie-triangles and tie-lines associated with three-phase, steam-injection problems in heterogeneous formations. The algorithms that capture the complex combinations of the appearance and disappearance of multiple phases are described in detail. The accuracy and computational efficiency of this negative-flash, tie-simplex based approach is demonstrated for several challenging compositional (CO2, sour-gas) and thermal-compositional (steam) models. The nonlinear behaviors are analyzed in terms of the particular displacement process, miscible/immiscible dynamics, number of components, and sensitivity to time step size.