bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Efficient and Practical Workflow for Probabilistic Forecasting of Brown Fields Constrained by Historical Data
Authors: Yang Chaodong , Nghiem Long , Erdle Jim , Moinfar Ali , Fedutenko Eugene , Li Heng , Mirzabozorg Arash , Card Colin 
Published: September 2015

Abstract
Brown fields are fields with significant production history. Probabilistic forecasting for brown fields requires multiple history-matched models that are conditioned to available field production data. This paper presents a systematic and practical workflow to generate an ensemble of simulation models that is able to capture uncertainties in forecasts, while honoring the observed production data.
The proposed workflow employs the Bayes theorem to define a posterior Probability Density Function (PDF) that represents model forecast uncertainty by incorporating the misfit between simulation results and measured production data. Previous workflows use the Markov Chain Monte Carlo (MCMC) sampling method, which requires an extremely large number (thousands) of simulation runs. To alleviate this drawback, a Proxy-based Acceptance-Rejection (PAR) sampling method is developed in this study to generate representative simulation models that characterize the posterior PDF using hundreds of simulation runs. The proposed workflow can be summarized in five key steps: Run an initial set of reservoir simulations by simultaneously varying multiple uncertain parameters using an experimental design method.Construct a proxy function using a Radial-Basis Function (RBF) neural network to approximate the posterior PDF calculated from the initial set of simulation results.Sample the posterior PDF using the PAR sampling method and run an ensemble of new simulation models using the sample values.The new simulation results obtained in step 3 are added to the training datasets generated in step 1 to improve the accuracy of the proxy function. Steps 3 and 4 are repeated until a predefined stop criterion is satisfied.Filter all simulation runs generated in step 3 using appropriate tolerance criteria for various history-match quality indicators. The selected filtered cases constitute the final ensemble of simulation models that can be further used for uncertainty quantification in forecasting.
The proposed workflow is demonstrated on two reservoir simulation models: Synthetic case. The forecast uncertainty of the ninth SPE Comparative Solution Project (SPE9) simulation model is investigated with a synthetic production history and 32 uncertain parameters.Unconventional oil field case. The workflow is applied to an Eagle Ford shale oil well to determine P90 (conservative), P50 (most likely), and P10 (optimistic) cases of estimated ultimate recovery (EUR).
Results of the workflow are compared to those obtained using the Metropolis-Hasting MCMC sampling method. The comparison shows that the proposed workflow only requires 800 simulation runs to obtain results as accurate as the MCMC method with 8000 simulation runs. This translates into a 10- times speedup, which makes the proposed workflow practical for many real reservoir simulation studies.
Modeling Fishbones Using the Embedded Discrete Fracture Model Formulation: Sensitivity Analysis and History Matching
Authors: Cavalcante Filho Jose Sergio , Xu Yifei , Sepehrnoori Kamy 
Published: September 2015

Abstract
The fishbones technology is a new well stimulation technique developed to increase well productivity index and improve reservoir connectivity to the well, being an alternative to hydraulic fracturing. This technique consists of creating several branches (holes) in the well using acid injection (dissolution and diversion). Those branches have small diameter and an average length of 40 feet. Main advantages of this technology over hydraulic fracturing are the competitive price and reduced operation time. In this paper we aim at modeling fishbones using the embedded discrete fracture model (EDFM), originally developed to model conductive faults and fractures. An EDFM preprocessing code was rewritten and extended to generate non-neighboring connections (NNC) between matrix, fractures and well connections; the NNCs were exported and used as input for a numerical simulator capable to handle NNCs. We modified the EDFM preprocessing code to adequately model fishbones. Each fishbone branch is treated as a fracture with dimensions equivalent to the branch dimensions (radius and length). The use of appropriate equations based on Peaceman's equation allows to model fishbones as equivalent fractures. Our new approach was used to perform sensitivity analysis (one at a time method) of the reservoir properties and the number of fishbones' branches for a case of primary oil production. A history match of the results of the first pilot using the fishbone technology was performed using an automated algorithm. Triple porosity cases were also evaluated and a good agreement between simulation and production data was obtained. A sensitivity analysis using design of experiments and the regression technique was used to compare the application of fishbones in different reservoirs (isotropic, anisotropic, and fractured) under primary oil production. The results of the simulations show that the fishbones is a promising stimulation technology that should be further evaluated.
Simulation of Fracture-to-Fracture Gas Injection in an Oil-Rich Shale
Authors: Zhu Peixi , Balhoff Matthew T. , Mohanty Kishore K. 
Published: September 2015

Abstract
Miscible gas injection is proposed here for improved oil recovery in unconventional, oil-rich shale reservoirs. The ultra-low permeability of shale makes injection from well to well difficult; thus it is proposed that gas is injected into a hydraulic fracture along a horizontal well and production occurs from an adjacent fracture, intersecting the same well. Compositional reservoir modeling was performed to investigate the effectiveness of the proposed gas injection scheme. The computational domain consists of two hydrofrac half-stages along a horizontal well to capture detailed information of the fluid flow near the well bore. The results show 15.7% OOIP incremental recovery for the base model with matrix permeability kmatrix = 10 μD over 5000 days (nearly 14 years) of CO2 injection, and 12.5% OOIP for the one with kmatrix = 1 μD, indicating that the gas injection scheme has the potential to vastly improve oil recovery in oil-rich shale formations.
The effects of reservoir properties and injection conditions on oil recovery were investigated by changing the injection pressure, reservoir heterogeneity, hydrofrac spacing, dispersion, and compositions of the injection gas. Increasing injection pressure leads to higher production before breakthrough and faster recovery of the oil in the stimulated region. Reducing the hydrofrac spacing has similar effect, although the production declines more rapidly after breakthrough. Introducing heterogeneity to the reservoir results in lower recovery, but the effect of spatial continuity (correlation length) on recovery is insignificant. It was also found that dispersion is mainly dominated by diffusion and mechanical dispersion is less important in most cases. Injection of hydrocarbon gas outperforms CO2, especially if the economics is also taken into account.
Addressing Forecasting Non-Uniqueness and Uncertainty in Unconventional Reservoir Systems Using Experimental Design
Authors: Collins P. W. , Badessich M. Fernandez , Ilk D. 
Published: September 2015

Abstract
Model-based production analysis using analytical or numerical models is not a new phenomenon and is considered a robust technique for analyzing and forecasting production data; however, its application to unconventional reservoir systems often proves problematic due to model non-uniqueness resulting from long-term transient flow regimes. This non-uniqueness, an unavoidable fact when analyzing inverse problems, is worsened by the uncertainty surrounding input model parameters when attempting to describe reservoir systems with a great deal of complexity (e.g. very low permeability, geomechanical effects, near-critical fluids, natural fracturing, etc.). The problem facing the engineer presents itself when different combinations of input parameters yield nearly identical history matches but very different time-rate profiles and estimated ultimate recovery (EUR) values when forecasting future production for a particular well.
A systematic framework that covers the full range of uncertainty for all relevant input parameters would clearly mitigate the ambiguity of production analysis and forecasting under uncertain conditions. In this work it is proposed that experimental design, which is a statistical technique used to describe or optimize a process by systematically analyzing the effect of the various controllable and uncontrollable factors of a system on an output (e.g. EUR), can provide such a framework. In this work, a methodology combining model-based production analysis with experimental design is used to history match and forecast fractured vertical and multi-fractured horizontal oil wells in the Vaca Muerta Shale with high-frequency time-rate-pressure data. The primary objectives of this work are to provide a comprehensive overview of the Vaca Muerta shale, outline experimental design as it relates to model-based production analysis, quantify uncertainties in model input parameters, and finally history match and forecast two wells that are producing in the Vaca Muerta Shale.
Phase Behavior and Flow in Shale Nanopores From Molecular Simulations
Authors: Jin Zhehui , Firoozabadi Abbas 
Published: September 2015

Abstract
Phase behavior and flow in shale nanopores, due to fluid heterogeneity, cannot be described by bulk and continuum-based formulations. The interactions between fluid and rock molecules are important in both phase behavior and flow. As a result, frameworks from bulk equations of state in phase behavior, and Knudsen diffusion and Klinkenberg slippage in flow may not have direct applications. Recently, we have studied both phase behavior and flow in nanopores using various molecular simulations. This work addresses a number of issues in relation to phase behavior and flow in nanopores. We model the excess adsorption of ethane in shale media. The data of ethane adsorption has been reported recently. Past data on hydrocarbon adsorption is limited to methane. We also model the effect of water on hydrocarbon adsorption in kerogen and compare the results with the effect in clay. In flow, as in our recent work, we use the dual control volume-grand canonical molecular dynamics (DCV-GCMD) simulations. We use a low pressure difference between high pressure and low pressure reservoirs connected to the nanopores. We find that similar to our past work, the flux of methane in the slit pores can be two orders of magnitude higher than the results from the Knudsen diffusion.
Theoretical Investigation of the Effect of Membrane Properties of Nanoporous Reservoirs on the Phase Behavior of Confined Light Oil
Authors: Zhu Ziming , Yin Xiaolong , Ozkan Erdal 
Published: September 2015

Abstract
This theoretical study is a first effort to probe the effect of semi-permeable membrane properties of nanopore networks on hydrocarbon phase behavior in tight-oil reservoirs. It is considered that the fluids stored in a nanoporous reservoir are divided into two parts: one part that is already "filtered" and can flow to a production well without compositional change, and another part that replenishes the "filtered" fluid according to the membrane efficiency of the nanopore network and the prevailing filtration pressure. This selective hydrocarbon transport leads to a compositional change in both of the "filtered" and "unfiltered" parts and changes other oil properties accordingly. The compositional change, fluid density, viscosity and interfacial tension are calculated as functions of pressure when the pressure decreases below the bubble point pressure of the "filtered" part. The findings of this work have ramifications on fluid saturation distributions and the composition of the trapped fluids at the beginning of a potential EOR application.
A Thorough Investigation of Mechanisms of Enhanced Oil Recovery by Carbonated Water Injection
Authors: Sohrabi Mehran , Emadi Alireza , Farzaneh Seyed Amir , Ireland Shaun 
Published: September 2015

Abstract
The benefits and advantages of waterflood are well-known with many decades of application in a wide range of reservoirs with different crude oil and rock types. However, the average global recover factor for waterflood is only around 30%. There is, therefore, great interest in developing methods that can augment waterflood and improve its recovery factor from the current low values. It has been shown that enriching water with CO2 and injecting it in the form of carbonated water can improve the performance of water flood significantly 1-15. However, a complete understanding of the pore-scale interactions and events taking place during carbonated water injection (CWI) in an oil reservoir and the actual mechanisms by which additional oil may be recovered are still missing and therefore the true potential of CWI is not yet well known. This is further complicated by the fact that the current commercial reservoir simulators are not able to adequately simulate the complex and multi-physics processes that take place during CWI which include both fluid/fluid and rock/fluid interactions.
The objective of the Carbonated Water Injection (CWI) JIP at Heriot-Watt University is to perform a thorough investigation of the performance of CWI under reservoir conditions and systematically study the parameters that impact the amount of oil recovery by CWI and its underlying mechanisms. Here we present the results of a series of CWI experiments performed under reservoir conditions at pore-scale and core-scale. Direct flow visualisation results of our high-pressure micromodel experiments reveal very vividly the pore-scale events that take place as CO2 gradually leaves the injected carbonated water and dissolves in the oil. The results show that the pore-scale interactions of carbonated water with crude oil are quite different from the well-known mechanisms observed in conventional CO2 flood. Apart from the usual CO2-related mechanisms such as oil swelling and viscosity reduction, in CWI, formation of a new fluid phase within the oil is observed. As we will show, this is a major mechanism that significantly improves the performance of CWI and the amount of additional oil recovery achieved by CWI. Our coreflood experiments confirm our pore-scale flow visualization results and clearly show that, compared to conventional waterflood, CWI can lead to substantial additional oil recovery under both secondary mode (injected instead of conventional water flood) and tertiary mode (injected after conventional water flood). The performance of CWI is significantly affected by the composition of the oil including the amount of light and intermediate hydrocarbons dissolved (solution gas) in crude oil.
Investigating Nano-Fluid Mixture Effects to Enhance Oil Recovery
Authors: Tarek Mohamed 
Published: September 2015

Abstract
Nano-particles have been investigated in the last few years as a promising technique for enhanced oil recovery at laboratory scale. Different metal oxides nano-particles have been tested solely in previous papers and some of these nano-particles increased the ultimate oil recovery.
This paper investigates the effect of mixing more than one nano-oxide in one dispersing fluid (to form a nano-fluid) on the ultimate recovery. Three nano-oxides were selected: Aluminum oxide (Al2O3), Iron oxide (Fe2O3) and Silicon oxide (SiO2). The selection of these oxides was based on the percentages of additional recovery each nano-oxide provided in literature and the mechanism that caused this increase in recovery. Each oxide is believed to increase recovery through different mechanism and combining different oxides with different recovery enhancement mechanisms may lead to further increase in ultimate recovery.
Three reference core flooding runs were performed in order to check the effect of each nano-oxide on the experimental core plugs ultimate recovery after water flooding. Different single nano-fluids were injected in each core until no more oil was produced. The same mixture of nano-fluids was then injected in the three cores resulting in more oil production in all cases (thus validating our concept).
To understand the different effects these nano-fluids may have on recovery, several experiments were conducted. These tests included three experimental runs with different mixture concentrations of nano-particles on a high permeability core starting directly with tertiary recovery (no water flood was applied before injecting the nano mixture).
The outcomes of these experiments showed that nano-fluid mixtures could be used as a better technique for EOR than single nano-fluid. Optimum nano-fluid mixture cocentration depends on both fluid and rock properties. The use of different slugs with different nano-fluids seems to benefit the recovery.
Mathematical Model of a Well, Draining Fractured Reservoir
Authors: Sergey Durkin 
Published: September 2015

Abstract
Well tests are an integral part of learning the filtration characteristics of the producing formation. The article considers the main approaches of learning and interpreting the results of field research on stationary and non-stationary filtration mode. The choice of one or another mathematical model predictions depends on the quality of filtration properties interwell reservoir. Heterogeneous, low-permeability reservoirs are special problem for the study of the mechanism of filtration. In the attempt to create a mathematical model of a well draining fractured porous reservoir, based on a realistic representation of fractures. The results of the adaptation field research confirmed the efficiency of real well developed numerical model. Established model allowed to interpret the radial, linear and bilinear flow regime. It is shown that the reservoirs are characterized by a linear and bilinear flow regime, indicating that the filtering mechanism in the system of “matrix-fracture” by different laws filtering. Also it developed a methodical approach that allows to take into account the wellbore, given technological regime on the head and on the bottom of the well. Three-dimensional formulation of the problem has allowed to extend the model to the multiphase flow.
Full Resolution Full Field Simulation Using Localized Computations
Authors: Sheth Soham M. 
Published: September 2015

Abstract
Locality is inherent to all transient flow and transport phenomena. Superposition of the two disparate spotiotemporal scales that underlie flow and transport leads to the problem of dimensionality. While the spatial locality in the temporal evolution of state variables is well-studied, little is known about the locality that is present over the course of individual Newton iterations that arise in the solution of an implicit timestep. This work derives a priori sharp and conservative estimates for the Newton update before its corresponding linear system has been solved. The current focus is the sequential implicit procedure for general nonlinear and heterogeneous two-phase flow in multiple dimensions. Due to the analytical nature of the work, the estimates are independent of the underlying spatial discretization. There are numerous applications of these estimates, including their use towards characterizing the convergence rate of Newton's method as a function of timestep size, or towards the development of scalable linear preconditioning strategies. This work focuses on applying the estimates to reduce the size of the linear system that is to be solved at each Newton iteration.
The key to the derivation of these estimates is in forming and solving the infinite-dimensional Newton iteration for the semidiscrete residual equations. In an implicit simulator, the Newton updates are accurate approximations to the continuous in space infinitedimensional updates. While the infinite dimensional updates are obtained by solving linear PDEs analytically, the discrete approximations are obtained by inverting a linear system. For flow, the analytical estimate for the Newton update is the solution of a linear constant coefficient screened Poisson equation. For transport, the estimate is the solution of a first-order linear PDE. The analytical solutions for these estimates are derived, and they can be applied computationally to any discrete problem.
In a simulation, at each nonlinear iteration, the estimates are evaluated over parts of the domain and they are subsequently used to identify the unknowns and cells that will undergo a Newton update that is larger than any prescribed tolerance. The reduced linear system is then formed for these unknowns only, and is solved to obtain the Newton update. Since the estimates are conservative, there is no degradation of the nonlinear convergence rate.
We present comprehensive large-scale computational results. The performance improvement using the proposed method directly depends on the extent of locality present as dictated by the physics. For problems with slight compressibility, the localization of the linear systems results in an order of magnitude of improvement in computational performance. On the other hand, incompressible models involve global pressure updates, and the locality is exploited in the transport part only.
A Simulation Study of Enhanced Oil Recovery Using Carbon Dioxide Foam in Heterogeneous Reservoirs
Authors: Tham Su Li 
Published: September 2015

Abstract
Conventional gas flooding suffers from poor sweep efficiency in heterogeneous reservoirs. In absence of mobility control, gas preferentially travels through the path of least resistance, bypassing oil in low permeability areas. Stable foams restrict flow in high permeability channels, diverting some of the flow to the lower permeability layers and allowing injected fluid to contact oil that would have been unswept by conventional gas floods. The objective of this research was to determine the extent of improvement caused by use of foam for CO2 floods in a range of heterogeneous reservoirs. Moreover, this study aims to provide a qualitative understanding of foam in heterogeneous reservoirs, which would help in designing successful CO2 foam flooding in enhanced oil recovery projects. The simulation study involves two-dimensional reservoir models with varying reservoir heterogeneity modeled by different Dykstra-Parsons coefficients (VDP). A surfactant-alternating-gas (SAG) scheme and a water-alternating-gas (WAG) scheme were carried out to determine the improvement of using foam in SAG compared to conventional WAG where foam was not present. A waterflood was also carried out to determine the incremental oil recovery of SAG and WAG over waterflood.
The CO2 breakthrough times, recovery factors, and sweep efficiencies based on pore volume injected were calculated from CMG SATRS simulation results. These factors were improved across all heterogeneities when foam was present in the system; however, there were important differences. More stable foam was formed in the reservoirs with the lowest heterogeneity, as shown by the largest increase in injector bottomhole pressure for the reservoirs with the lowest VDP. The improvement in breakthrough time increased as reservoir heterogeneity increases. The breakthrough time was increased by 11.5% for reservoirs with the lowest VDP and 22.0% for reservoirs with the highest VDP. Foam lessened the severity of channeling and gravity segregation in reservoirs and improved vertical sweep. However, in the more heterogeneous cases, there were sections of the reservoir that remained unswept by CO2 even for SAG floods. The greatest improvement in terms of stock tank barrels of oil recovered from using SAG occurred for the most heterogeneous reservoirs. Compared to waterfloods, SAG floods recovered an additional 41.2% of OOIP on average, which was 4.5% OOIP more than conventional WAG floods. Thus, the use of foam was more economical in reservoirs with greater heterogeneities.