bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boundary Segments for Multisegment Well Models
Authors: Stone Terry , McKee Francois , Istchenko Christopher 
Published: March 2019

Abstract
Petroleum recovery from oilfield assets increasingly involves wells that are very long in extent and have multiple laterals, multiple tubing strings and multiple control points to prevent breakthrough of unwanted fluids and/or to optimize recovery. Instead of simply controlling rates at the wellhead, downhole devices are now available where apertures and other controlling parameters can be set statically, autonomously, or through surface intervention,. Having various control points in a wellbore that may include numerous flow paths requires a flexible setup and robust algorithms to effectively set all local constraints at various measured depths. This paper describes special constructs called "boundary segments" with a similar set of flow rate and pressure control modes to those available for tubinghead or bottomhole well control. In a multisegment well model whose topology consists of a set of nodes with intrinsic properties such as pressure, global mole fractions, total enthalpy, saturations, etc. and a set of pipes with attributes of length, volume, and a flow rate, these special segments share an existing node but have their own unique pipe together with boundary conditions and an accompanying set of control modes.
Boundary segments are highly flexible, elegant, easy to implement, and useful in a variety of cases. This paper will provide reservoir simulation engineers and developers with an understanding of a simple method to calculate primary well control at the surface choke together with multiple downhole constraints from devices and tubing strings.
Implementation of Physics-Based Data-Driven Models With a Commercial Simulator
Authors: Ren Guotong , He Jincong , Wang Zhenzhen , Younis Rami M. , Wen Xian-Huan 
Published: March 2019

Abstract
The use of full-physics models in close-loop reservoir management can be computationally prohibitive as a large number of simulation runs are required for history matching and optimization. In this paper we propose the use of a physics-based data-driven model to accelerate reservoir management and we describe how it could be implemented with a commercial simulator.
In the proposed model, the reservoir is modeled as a network of 1D flow paths connecting perforations at different wells. These flow paths are discretized and the properties at each grid block along each flow path are derived from history matching of production data. To simulate flow in this network model through a commercial simulator with all the physics, an equivalent 2D Cartesian model is set up in which each row corresponds to one of the 1D flow paths. Finally, the history matching is performed with ensemble smoother with multiple data assimilation (ESMDA).
The proposed network model is tested on both waterflood and steamflood problems. It is demonstrated that the proposed model matches with well-level production history (including pressure and phase flow rate) well. The calibrated ensemble from ESMDA also provided a satisfactory probabilistic forecast of future production that almost always envelops the true solutions. This indicates that the proposed model, after calibrated with production data, is accurate enough for production forecast and optimization. In addition, the use of commercial simulator in the network model provided flexibility to account for complex physics, as demonstrated by the successfully application to the steamflood problem. Compared with traditional workflow that goes through the full cycle of geological modelling, history matching and probabilistic forecasting, the proposed network model only requires production data and can be built within hours. The resulted network model also runs much faster than a full-physics as it typically has much less grid blocks. We expect the proposed method to be most useful for mature fields when abundant of production data is available.
As far as we know, this is first time a physics-based data-driven model is implemented with a commercial simulator. The use of commercial simulator makes it easy to extend the model for complex reservoir such as thermal or compositional reservoirs.
Closed-Loop Stochastic Oilfield Optimization Under Uncertainty in Geologic Description and Future Development Plans
Authors: Jahandideh Atefeh , Jafarpour Behnam 
Published: March 2019

Abstract
Development and management of oilfields involve several sources of uncertainty that complicate an already challenging decision-making process. Two main sources of uncertainty are related to geologic description of reservoirs and future development scenarios. While geologic uncertainty has been widely studied and robust optimization methods have been developed to account for it, the uncertainty in future development plans has not been considered in optimization problems. Future development strategies have been included as decision variables in field development optimization problems. However, in practice, future field development plans tend to deviate from the solutions obtained in past optimization problems. Therefore, a more prudent and realistic approach toward oilfield optimization is to consider the uncertainty in both geology and future development plans to obtain robust solutions. We develop a closed-loop stochastic field development optimization formulation to account for the uncertainty in geologic description and future infill drilling scenarios. The proposed approach optimizes the decision variables for current stage of planning (e.g. well locations and operational settings) while accounting for geologic and future development uncertainties, where the former uncertainty is represented by using several reservoir model realizations while the latter uncertainty is represented through drilling scenario trees and probabilistic description of future drilling events/parameters. In the developed method, prior to each decision-making stage the reservoir is operated based on the current optimal strategy until dynamic data becomes available to calibrate the geological models. After each data assimilation step, a new optimization is performed to adjust controllable decision variables for the current well configuration (e.g., well rates or BHPs) using the updated models and potentially revised future development scenarios. Using a multi-stage stochastic optimization workflow this process is repeated after each decision stage. Several numerical experiments are presented to discuss various aspects of the proposed closed-loop stochastic optimization formulation and to compare the solutions from different methods adopted for treatment of future development plans. The results indicate that stochastic treatment of future development events (1) can hedge against uncertain future development activities by obtaining optimization solutions that are robust against changes in future decisions, and (2) considerably reduces the performance losses that can result from field development when uncertainty is disregarded.
Coupled Numerical Simulation of Transient Microseismicity and Flow in Fractured Reservoirs
Authors: Han Zheng , Ren Guotong , Younis Rami M. 
Published: March 2019

Abstract
An XFEM-EDFM scheme and associated monolithic solution method are proposed to model time-dependent poromechanics and two-phase flow. Fractures are modeled as interfaces with displacement discontinuities. The contact forces are treated using Lagrange Multipliers. A number of numerical tests are performed to investigate the Newmark scheme's accuracy and cases for wave propagation in poroelastic and natural fracture media are implemented to evaluate computational efficiency. We apply the method to model seismic data from hydraulic fracture network. Empirical results validate the Newmark scheme accuracy as well as computational efficiency and localization of newton update in seismic field is necessary for the further application. The synthetic model of multiple hydraulic stages illustrates the effect of flow coupling and newly generated fractures on the microseismic field. The model is applied to simultaneously assimilate well performance and microseismic observations, thereby informing about the causal event dynamics.
Ranking Fractured Reservoir Models Using Flow Diagnostics
Authors: Spooner Victoria , Geiger Sebastian , Arnold Dan 
Published: March 2019

Abstract
This paper describes the application and testing of innovative dual porosity flow diagnostics to quantitatively rank large ensembles of fractured reservoir models. Flow diagnostics can approximate the dynamic response of multi-million cell models in seconds on standard hardware. The need for new faster screening methods stems from the challenge of making robust forecasts for naturally fractured carbonate reservoirs. First order uncertainties including the distribution and properties of natural fractures, matrix heterogeneity and wettability can all negatively impact on recovery. A robust multi-realisation approach to production forecasting is often rendered impractical due to the time cost for simulating many models.
We have extended existing flow diagnostics techniques to dual porosity systems by accounting for the matrix-fracture exchange. New metrics combine the transfer rate with the advective time of flight in the fractures identifying risk factors for early water breakthrough and providing quantitative measures of dynamic heterogeneity.
We have compared ranking a large ensemble of synthetic fractured reservoir models using dual porosity flow diagnostics and using full-physics simulation. The synthetic ensemble explores a number of different geological concepts around the fracture distributions, wettability and matrix heterogeneity which can. Not only does the flow diagnostic ranking agree well with the cumulative oil ranking the run time for the flow diagnostics is &lt;0.25% of the total simulation time. This significant reduction in the time to compare models allows more time to spend running full physics simulation on the important and geologically diverse cases that offer the most insight.
Numerical Simulation of Matrix Acidizing in Fractured Carbonate Reservoirs Using Adaptive Enriched Galerkin Method
Authors: Dong Rencheng , Lee Sanghyun , Wheeler Mary 
Published: March 2019

Abstract
Acidizing in un-fractured carbonate reservoirs has been well studied through modeling and simulation. Since carbonate reservoirs are often naturally fractured, fractures should be modeled for realistic acidizing operations. We present adaptive enriched Galerkin (EG) methods to simulate acidizing in fractured carbonate reservoirs. We adopt a two-scale continuum model for the acid transport. The coupled flow and reactive transport systems are spatially discretized by EG methods. Fractures are introduced using local grid refinement (LGR) technique. Adaptive mesh refinement (AMR) is implemented around wormhole interfaces. Simulation results show that acidizing in fractured carbonate reservoirs is largely dependent on the fracture system while acidizing in unfractured carbonate reservoirs is mainly determined by operation parameters such as acid injection rate. Computationally, the proposed EG scheme has less numerical dispersion and grid orientation effects than standard cell center finite difference/volume methods. AMR is very efficient to track the wormhole growth and speed up acidizing simulations.
Tight Oil and Shale Gas PVT Modelling for Flow Simulation with Matrix-Fracture Interaction
Authors: Sobecki Nicolas , Wang Shihao , Ding Didier-Yu , Nieto Draghi Carlos , Wu Yu-Shu 
Published: March 2019

Abstract
Tight oil and shale gas reservoirs have a significant part of their pore volume occupied by micro (below 2nm) and mesopores (between 2 and 50nm). This kind of environment creates strong interactions forces in the confined fluid with pore walls as well as between its own molecules and then changes dramatically the fluid phase behavior and its thermodynamic properties. Pressure-Vapor-Temperature (PVT) modeling of such fluids becomes therefore a challenge in order to get accurate production forecast reservoir simulations. Furthermore along the flow from the matrix to the well through the fractures, the fluid will pass through a very heterogeneous pore size distribution which will alter it differently according to the pore size and the spatial distribution. An important work has therefore to be done on developing upscaling methodology of the pore size distribution for large scale reservoir simulations. Firstly molecular simulations will be performed on pure components and mixtures in order to get reference thermodynamic properties at liquid/vapor equilibrium for different pore sizes. The comparison with commonly used modified equation of state (EOS) in the literature highlighted the model of flash with capillary pressure and critical temperature and pressure shift as the best one to match reference molecular simulation results. Secondly fine grid matrix/fracture simulations have been built and performed for different pore size distributions. The study has shown that the pore size distribution has an important impact on reservoir production and that this impact is highly dependent of the volume fraction of nanopores inside the matrix. Capillary pressure heterogeneity and pore radius dependent EOS cause gas flow slowdown or gas trapping inside the matrix and postponed gas flow apparition in the fractures during depletion which reduce the GOR (Gas-Oil Ratio) at the well. Coarse grid upscaling models have then been performed on the same synthetic case and compared to the reference fine grid results. The commonly used upscaling methodology of dual porosity model with average pore radius for the pore size distribution is unable to match the fine grid results. A new triple porosity model considering fracture, small pores and large pores with their own capillary pressure and EOS, together with MINC (Multiple Interacting Continua) approach, has shown very good match with the reference fine grid results. Finally a large scale stimulated reservoir volume with different pore size distribution inside the matrix has been built using the upscaling method developed here. The proposed triple porosity methodology is able to model the PVT of the confined fluid and its flow across a very heterogeneous pore size distribution up to the well through fractures in a large scale reservoir simulation.
Higher Resolution Unstructured Spectral Finite-Volume Method for Flow in Porous Media
Authors: Xie Yawei , Edwards Michael G. 
Published: March 2019

Abstract
A novel higher resolution spectral volume method coupled with a control-volume distributed multi-Point flux approximation (CVD-MPFA) is presented on unstructured triangular grids for subsurface reservoir simulation. The flow equations involve an essentially hyperbolic convection equation coupled with an elliptic pressure equation resulting from Darcy's law together with mass conservation. The spectral volume (SV) method is a locally conservative, efficient high-order finite volume method for convective flow. In 2D geometry, the triangular cell is subdivided into sub-cells, and the average state variables in the sub-cells are used to reconstruct a high-order polynomial in the triangular cell. The focus here is on an efficient strategy for reconstruction of both a higher resolution approximation of the convective transport flux and Darcy-flux approximation on sub-cell interfaces. The strategy involves coupling of the SV method and reconstructed CVD-MPFA fluxes at the faces of the spectral volume, to obtain an efficient finer scale higher resolution finite-volume method which solves for both the saturation and pressure. A limiting procedure based on the Barth-Jespersen limiter is used to prevent non-physical oscillations on unstructured grids. The fine scale saturation/concentration field is then updated via the reconstructed finite volume approximation over the sub-cell control-volumes. The method is also coupled with a discrete fracture model. Performance comparisons are presented for tracer and two phase flow problems on 2D unstructured meshes including fractures. The results demonstrate that the spectral-volume method achieves further enhanced resolution of flow and fronts in addition to that of achieved by the standard higher resolution method over first order upwind, while improving upon efficiency.
A General Framework Model for Fully Coupled Thermal-Hydraulic-Mechanical Simulation of CO2 EOR Operations
Authors: Wang Shihao , Di Yuan , Wu Yu-Shu , Winterfeld Philip 
Published: March 2019

Abstract
In this work, we present the development of a comprehensive mathematical formulation and reservoir simulator for thermal-hydraulic-mechanical simulation of CO2-EOR processes
We adopt the integral finite difference method to simulate coupled thermal-hydraulic-mechanical processes during CO2-EOR in conventional and unconventional reservoirs. In our method, the governing equations of the multiphysical processes are solved fully coupled on the same unstructured grid. A multiscale algebraic linear solver is adopted to speed up the non-isothermal flow calculation. Inspired by the meshless method, the algebraic solver eliminates the low-frequency terms through smoothing on a coarse grid. In order to simulate the phase behavior of a three-phase system, a three-phase flash calculation module, based on direct minimization of Gibbs energy, is implemented in the simulator.
We have investigated the impact of cold CO2 injection on injectivity as well as on phase behavior. We conclude that cold injection is an effective way to increase injectivity in tight-oil reservoirs. We have observed and studied the temperature decreasing phenomena near the production well, known as the Joule-Thomson effect, induced by expansion of in-situ fluids.
The novelty of this work lies in the fully coupled simulation scheme, including non-isothermal effects on CO2-EOR processes and recoveries, which has been ignored in almost all modeling studies of CO2-EOR. The multiscale solution strategy and the unique phenomena of non-isothermal compositional modeling coupled with geomechanics are captured by our simulator.
Recent Developments in Unstructured Aggregation-Based Upscaling for Simulation Workflows and Applications
Authors: Thomas Sunil , Du Song , Dufour Gaelle , Mallison Brad , Muron Pierre , Rey Alvaro 
Published: March 2019

Abstract
New developments in unstructured aggregation-based upscaling are presented that improve the flexibility of coarsening designs and enable a more integrated reservoir simulation workflow. Field cases and synthetic tests demonstrate the advantages of the method compared to legacy upscaling methods and fine scale simulations.
Aggregation-based upscaling has recently emerged as a favorable alternative to conventional upscaling methods in reservoir simulation workflows. We outline these developments and describe algorithms used to compute flexible aggregation schemes, coarse transmissibility, and upscaled well indices. The main value additions are,
the ability to selectively coarsen and adapt areal and vertical resolution based on geological features, areas of interest, and/or stratigraphic layer metrics resulting in improved accuracy, the improved simplicity and robustness resulting from avoiding the explicit creation of coarse grids and maintaining one grid for earth modeling and reservoir simulation workflows, and the broad applicability to fields modeled by many grid types including unstructured grids and discrete fracture models.
The aggregation-based upscaling methodology is tested in the simulation of some synthetic benchmarks, and of full field models. Comparisons are provided to fine scale simulations in each case, and to legacy upscaling simulations, wherever practically feasible. The most important findings are the seamless integration afforded by the new workflow by eliminating the need for the coarse simulation grid, the significant savings in user interaction time and computational time, and the overall improvement in accuracy, when compared to legacy upscaling workflows. This is important because reservoir engineers operate on tight deadlines to complete projects, and because the logistical challenges of handling fine and coarse grids are significant for studies that involve multiple reservoir model realizations.
Robust Multi-Objective Field Development Optimization for the Mariner Asset
Authors: Hanea Remus Gabriel , Bjorlykke Ole Petter , Hashmi Yastoor , Feng Tao , Fonseca Rahul Mark 
Published: March 2019

Abstract
In this paper we present our results, challenges and learnings, over a two-year period wherein robust multi-objective optimization was applied at the Mariner asset which is being currently developed. Many different problems were solved with different objectives. These problems were formulated based on the phases of planning and development at the asset. The optimization problems include drilling order and well trajectory optimization as the main objectives with reduction in water cut and reduction of gas production to minimize flaring as secondary objectives. We use the efficient stochastic gradient technique, StoSAG, to achieve optimization incorporating geological and petrophysical uncertainty. For some problems computational limitations introduced challenges while for other problems operational constraints introduced challenges for the optimization.
Depending on the problems significant increases between 5% and 20% in the expected value of the objective function were achieved. For the multi-objective optimization cases we show that non-trivial optimal strategies are obtained which significantly reduce (40% decrease) gas production with minimal loss (less than 1%) in the economic objective. Our results illustrate the importance of flexible optimizations workflows to achieve results of significant practical value at different stages of the planning and development cycle at an operational asset.