bluuebunny/crossref_metadata_2025_split huggingface dataset:
Injection Well Rate and Pressure Analyses Suggest Practical Waterflood Improvements
Authors: Swanson G. S. 
Published: April 2018

Abstract
Waterflood injection wells operate at maximum efficiency when delivering maximum, non-fracturing matrix rates to highest oil water ratio (OWR) subzones. Decreasing OWR observed during the later years of a mature waterflood intensifies need for analysis and optimization of injection efficiency. Analyses of injection rates, pressures and distribution profiles, especially when combined with recently more available step rate test (SRT) data allow injector efficiencies to be quantified in terms of estimated resulting BOPD.
The Los Angeles basin is home to many mature, low OWR waterfloods and a large, steadily increasing number of injection wells. In order to analyze injection efficiency over time, a prototype injection well, designed to include features common to LA basin injectors, was evaluated at key times of design, SRT, startup, profile deterioration, and finally, 100% point exit.
Local DOGGR injector permitting practices were incorporated into determination of "Maximum Allowable Surface Pressure" (MASP) for the prototype well. Estimated losses of injection capacity resulting from conservative "safety" practices of frac gradient discounting and ignoring friction pressure were significant, suggesting consideration of alternative uses of SRT data.
Damage/stim cycling, an unfortunately common LA basin injector operational practice, was analyzed in detail, focusing on inefficiencies resulting from damage accumulation followed by unintentional selective stimulation of lowest priority subzones. Since the industry's common goals would be advanced by a basin wide decrease of damage/stim cycling, improvements are suggested for the consideration of both operators and regulators.
Operators with best record for maximizing injection efficiency reduce damage/stim cycling by maintaining appropriate water quality standards and optimized injection profiles. When coupled with aggressive production well management policies which minimize low OWR production, e.g., shutting in highest water cut wells, even very mature waterfloods have been shown to perform without rapid BOPD declines.
Paper concludes with practical suggestions to accomplish DOGGR/UIC fracture-prevention goals utilizing traditional and/or modified SRT designs to generate a permitted "Maximum Allowable Rate" (MAR). In addition to avoiding unintended consequences of the traditional MASP permitting approach, waterflood management and regulation by MAR would encourage development of new technologies and operational practices.
Dynamic Layered Pressure Map Generation in a Mature Waterflooding Reservoir Using Artificial Intelligence Approach
Authors: Li Yuanjun , Popa Andrei , Johnson Andrew , Ershaghi Iraj , Cassidy Steve 
Published: April 2018

Abstract
In this paper, we present an Artificial Neural Network (ANN) solution approach to estimate average reservoir pressure from partial data recorded from fall-off tests. The methodology, while relatively simple, is entirely based on calibrating data from well tests with full fall-off information. Compared with conventional reservoir pressure estimation models, which usually require a long shut-in time and manual analysis for an individual well, this approach provides an efficient way of processing large data sets. Using data from injection well fall-off tests can avoid cost from non-producing periods of production wells. Also, utilizing injection profile tracers with shut-in pressure trends at the surface, we can infer the sand face pressure trends assuming a hydrostatic column during a shut-in period, greatly reducing instrumentation costs and downhole jewelry requirements.
This methodology is extremely helpful for mapping average pressure around injection wells in a reservoir with hundreds of injection wells with multiple flow units. In principle, maps generated from fall-off tests can be used as diagnostic tools to assist in formulating water flooding plans, ameliorating oil production capability, arranging well pattern density and preserving reservoir stability by providing an overview of internal oilfield conditions. Because of its practical simplicity and maneuverability, this new methodology can rapidly offer actionable data and generate remarkable business value.
Applying a Combined Hydraulic Fracturing, Reservoir, and Wellbore Simulator: Staged Field Experiment #3, Cluster Spacing, and Stacked Parent/Child Frac Hits
Authors: McClure Mark W. , Kang Charles A. 
Published: April 2018

Abstract
This paper describes three applications of a fully integrated hydraulic fracturing, reservoir, and wellbore simulator. The simulator describes hydraulic fracturing, shut-in, and production in a single continuous simulation. It describes multiphase effects (using either the black oil model or a compositional fluid model), thermal effects, transport of tracers and/or non-Newtonian fluid additives, stress shadowing from fracture propagation, and poroelastic stress effects from depletion, and uses a detailed proppant transport algorithm. It uses constitutive relations that smoothly transition from equations for flow through an open crack to equations for flow through a closed crack (with or without proppant). In the first example, we build a simulation model of Staged Field Experiment #3, a well-known historical dataset. Our result is compared with other published simulations and is matched to 15 years of production data. The simulation shows how the transport and settling of proppant in the fracture during injection and shut-in are impacted by processes such as clustered and hindered settling. Gel crosslinking and breaking are described with first-order reaction rate constants. In the second example, we perform a sensitivity analysis on cluster spacing in a generic slickwater fracturing treatment in a horizontal well. The simulations show complex interactions between stress shadowing, fracture propagation, proppant transport, and multiphase flow. The sensitivity analysis indicates that minimizing near-wellbore pressure drop is critical for improving production. Closer cluster spacing decreases near-wellbore pressure drop by providing more conduits for flow. In the third example, we simulate a vertically stacked parent/child scenario. Depletion of the overlying parent well leads to upward propagation from the child well and direct frac hits. The frac hits remobilize proppant as water sweeps into the parent well fractures, displacing gas. In the appendix, we summarize a suite of validation simulations that confirm the numerical accuracy of the simulator.
Remediation Solutions for Lost Circulation Using Case Based Reasoning
Authors: Reedy K. , Popa A. S. , Cassidy S. D. 
Published: April 2018

Abstract
Lost circulation represents a very costly, time consuming challenge to drilling through depleted geological zones that has proven difficult to accurately predict and manage. The standard approach relies on the driller's experience with the field to know how best to treat lost circulation when it occurs, or better yet, avoid it altogether, usually by enforcing maximums and minimums to various drilling parameters. This approach, however, ignores the key interplays between all of the variables involved, geological and reservoir performance information in addition to drilling data, where a change in one variable may affect the safe operating range of another. Taking all variables into account can be a prohibitively arduous task, particularly while managing the many other demands of drilling operations. Fortunately, a computer can quickly make all of the necessary calculations, and with programs designed to mimic human decision-making, can even make recommendations. The aim of this project was to create a program that would take into account all of the key variables related to lost circulation and provide drillers in the field on-the-spot recommendations as to the most successful method of remediation, and to provide proof of concept that a such programs could be created to help prevent lost circulation in the first place. The objective was achieved by creating a system using Case-Based Reasoning, which reviews a database of past incidents, determines those most similar in nature, and provides recommendations based on previous successes and failures. This program, when run on test cases, was able to accurately recommend the proper lost circulation remedial method. This paper will cover details on the types of data used, the operating mechanics of this system, example cases, and a detailed breakdown of the results.
Modeling Coupled Nonisothermal Reservoir/Wellbore Flow Behavior in Gas Reservoir Systems
Authors: Xu B. , Kabir S. , Hasan A. R. 
Published: April 2018

Abstract
Most analytical and numerical flow modelling presuppose isothermal flow behavior in the reservoir. However, for high rates and large consequent drawdown gas reservoirs, the nonisothermal behavior becomes the norm due to the Joule-Thomson (J-T) effect. Other factors, such as a fluid's adiabatic expansion (AE), heat convection, and the heat exchange with surrounding formations may also make contributions. Accounting for this nonisothermal flow behavior becomes a necessity for accurately estimating a wells's performance due to changes in fluid properties and also from the standpoints of wellbore flow assurance and its mechanical integrity.
This paper starts with the general energy balance in the reservoir and presents a semianalytical solution to estimate the nonisothermal, single-phase gas temperature in the reservoir during production. This solution considers the J-T effect, adiabatic expansion effect, transient temperature behavior, heat convection, and heat exchange of fluid with over and under-burden formtions. The variations of gas viscosity, density, J-T coefficient as a function of temperature and pressure are taken into consideration by making a small spatial step at each computional node. A field case study validates the time-variant wellbore temperature profiles with the coupled reservoir heat transfer model. Distributed temperature measurements during a drill stem test (DST) made this validation feasible.
The J-T effect dominates in the near wellbore region due to dramatic pressure change. The J-T induced cooling effect is usually happened for gas in the reservoir. However, for high-pressure systems, the gas behaves like a liquid and gets heated up. For some intermediate pressure intervals, the gas temperature slightly increases with expansion, reach a plateau, and then gradually decreases as the gas moves toward the wellbore with declining pressure. By coupling the reservoir heat transfer model with the wellbore heat transfer model, one can monitor both production and flow assurance related issures that may arise either from thermodynamic solids or tubular mechanical integrity.
Sensitivity Analysis for Solar-Generated Steam for Enhanced Oil Recovery
Authors: Roig R. , Agarwal A. , Kovscek A. R. 
Published: April 2018

Abstract
Increasing regulations on greenhouse gas emissions (GHG) and fluctuations in the price of natural gas are driving innovation for crude-oil production methods. Solar-generated steam has the promise to reduce by up to 80% of GHG emissions in areas of abundant solar insolation. There are cyclic fluctuations in the steam injection rate associated with sunlight hours and seasonal variations that create the risk of temperature and pressure fluctuations along the wellbore. This paper analyzes the recovery efficiency of the steam injection process for solar-generated steam supplemented with conventional steam.
The viability of solar thermal enhanced oil recovery (TEOR) was evaluated using data from the San Joaquin Valley in California as input to a commercial reservoir simulator. The efficiency was quantified through reservoir simulation using a layered homogeneous 3D grid and corresponding economic analysis. Reservoir simulations with variable steam rate, quality, and temperature of diurnal and nocturnal steam injection were conducted. Various injection schedules and reservoir responses were analyzed, including the geomechanical response for continuous variable rate injection. The economic analysis was based on the operating expenses, mainly heating, lifting, and maintenance costs per unit of oil extracted.
This research shows that reducing the dependency on conventional steam using a minimum nocturnal steam rate contributes to better energy efficiency. Also, reducing the steam quality by up to 50% percent in both diurnal and nocturnal injection presented a promising cost-effective solution despite reducing somewhat the amount of oil recovered. We also discovered that reducing the nocturnal steam temperature provided substantial economic benefits with only a minor impact on the cumulative oil recovered. The geomechanical reservoir deformation triggered by steam pressure and temperature variations was within reasonable limits and did not present causes for concern. This economic analysis was done assuming an already paid out capital expense, both for solar and conventional steam. We compute the Net Present Value (NPV) of the profits using multiple price scenarios to compare the different cases. The maintenance cost and efficiency degradation for the solar generated steam is not considered in the absence of any available long term industry data. An optimal injection schedule and conventional steam contribution can be engineered based on the field operating and economic requirements.
An Improved Probability Conditioning Method for Constraining Multiple-Point Statistical Facies Simulation on Nonlinear Flow Data
Authors: Ma W. , Jafarpour B. 
Published: April 2018

Abstract
We evaluate the use of facies probability maps for conditioning discrete multiple-point statistical (MPS) facies simulation on dynamic production data. In MPS simulation, conditional probabilities are estimated from a training image (TI), a conceptual model of geologic connectivity, and used to draw samples of facies distributions that are statistically consistent with those encoded in the TI. Whereas conditioning MPS simulation on both static hard data (e.g., well logs) and soft data (e.g., seismic) is straightforward, calibration of facies against nonlinear flow data is nontrivial. The use of facies probability maps for conditioning MPS simulation on dynamic production data presents a promising approach for calibration of complex facies models. We present an overview of MPS-based conditional simulation with probability maps and discuss some of the important properties and implementation issues of this approach. The paper presents two important contributions: (1) improvement of the original probability conditioning method (PCM) by constructing the facies probability maps based on the first and second order statistical moments of the updated permeabilities at each cell; (2) generalization of the "tau" model to include pixel-based τ values that can assign different confidence levels to the facies probabilities at different grid blocks. Results from numerical examples demonstrate that the proposed approach outperforms the original PCM by incorporating additional information from the observed dynamic data into MPS-based facies simulation.
Agile-Scrum for Facility Design Project Management
Authors: Sljivar I. , Gunasekaran A. 
Published: April 2018

Abstract
Agile-Scrum (AS) Project Management, which originated in the IT industry, has unlimited potential to benefit both operating and service companies in oil and gas industry and many others. This paper will show how it could be applied to facility design work as a framework to improve the quality, timeliness and overall value of delivering construction drawings. The outcome that could be expected from this is less change orders and delays during the construction and much more satisfied operation teams. The design and construction of facilities is a complex work that requires close collaboration between multidisciplinary teams. AS framework enables this collaboration by creating a safe engaging environment in which self-organizing teams can find the best ways to achieve project requirements through incremental and prioritized value delivery. The goal of AS is to first focus on critical work to minimize the project risk and then maximize the benefit to the customer, in this case construction and operation teams, through continuous feedback loops. There are three main team roles that will be described in this paper: Scrum Master, Product Owner, and Development (Design) Team.
Effect of Stress Shock and Pressurization/Depressurization Hysteresis on Petrophysical Properties of Naturally-Fractured Reservoir Formations
Authors: Civan F. 
Published: April 2018

Abstract
This paper presents a theoretically rigorous formulation and correlation of the effect of poroelasticity on stress-dependent petrophysical properties of naturally-fractured reservoirs, including porosity, permeability, relative permeability, and capillary pressure, by consideration of the stress shock effect across a critical effective stress and the pressurization/depressurization hysteresis. This model accounts for the deformation, transformation, deterioration, and collapse of the pore structure during pressurization and depressurization processes and their effects on the properties of naturally-fractured reservoir formations. A stress shock is shown to occur in naturally-fractured reservoir formations at a critical stress during transition between open and closed natural fractures in loading and unloading applications. The effect of the stress shock and pressurization/depressurization hysteresis on petrophysical properties of reservoir formations is formulated by means of a modified power-law equation derived from a phenomenological model referred to as a rate equation. The modified power-law equation is shown to alleviate the shortcomings of the ordinary power-law equation applied in many studies.
The comprehensive model developed in this study is validated by means of various experimental data gathered by testing of samples from sandstone, carbonate, and shale reservoirs. The phenomenological parameters of the rock samples are determined for best match of experimental data. The scenarios examined in this study indicate that pressurization/depressurization hysteresis has a significant effect on the stress-dependent porosity and permeability of reservoirs. The model developed in this paper can describe the stress-dependent porosity and permeability of the fractured rock formations much more accurately than the commonly used empirical correlations. The accurate methodology presented for proper correlation of stress-dependent properties of reservoir formation rocks honors the slope discontinuity at a yield or critical effective stress. The stress-dependency of rock properties are described by the modified power-law expressions separately over the low stress region below the critical stress and the high stress region above the critical stress. The proposed data correlation methodology is proven to be highly effective in the analyses and correlations of the experimental data of various types of reservoir rock formations as indicated by the correlations achieved with significantly high coefficients of regressions very close to the unity.
Unsupervised Statistical Learning with Integrated Pattern-Based Geostatistical Simulation
Authors: Li Q. , Aguilera R. 
Published: April 2018

Abstract
This study presents a new geostatistics modeling methodology for the purpose of achieving the following three objectives. (1) Connecting geostatistics and machine learning methodologies, (2) Using non-linear topological mapping to reduce the original high dimensional data space to low dimensional subspace, as well as clustering for identifying and extracting meaningful patterns for both visualization and efficiency purposes, and (3) Using unsupervised learning algorithms to bypass potential problems encountered while using supervised learning algorithms.
Past observations have indicated that due to lack of labeled input data, artificial neural network (ANN) architecture, based on feedforward and backpropagation supervised learning, is difficult to apply.
To eliminate this difficulty and accomplish the 3 aforementioned objectives we introduce in this paper TopoSim, a neural topology-preserving based geostatistical simulation algorithm, which integrates (1) Self-Organizing Map (SOM) and its updated version, Growing Self-Organizing Map (GSOM), and (2) ANN with an unsupervised competitive learning structure. The proposed simulation integrates in a single step dimensionality reduction and extraction of input data structure pattern. Connectivity between geostatistical simulation problems and machine learning tasks are explained and constructed for the first time.
We perform TopoSim unconditioned geostatistical realizations, which show improvements in continuity and pattern reproduction when compared with previously developed single normal equation simulation (SNESIM) algorithms.
We conclude that the geostatistical simulation task is essentially a machine learning problem, i.e., getting the model to learn from available data and subsequently using the model for prediction purposes.
High Resolution Hydraulic Fracture Network Modeling Using Flexible Dual Porosity Dual Permeability Framework
Authors: Yang D. , Xue X. , Chen J. 
Published: April 2018

Abstract
Advancement of multistage hydraulic fracturing technology made unconventional reservoirs (UCR) development economically very attractive. Accurate and efficient production forecasts from UCR are challenging because of the complexity of the fracture network. Abstractions inherent in the traditional dual porosity dual permeability (DPDK) model makes it inadequate to simulate UCR. Discrete Fracture Model (DFM) provides better resolution of fracture geometry but it is not widely used in the industry because it is computationally expensive and history matching is difficult to perform.
This paper presents a new option which utilizes the dual medium framework from traditional DPDK modeling and incorporates effects of each fracture explicitly as it is done in the DFM approach. Single medium is used to model the matrix where there is no fracture present, and dual medium is used to model the fracture network and matrix. This method takes advantage of the optimized DPDK feature in existing commercial simulators. In the near wellbore areas where fractures exist, matrix-fracture coupling is calculated using the same equation as the Embedded Discrete Fracture Model (EDFM). Additionally, to increase accuracy, high resolution local grid refinements (LGRs) are adopted at fracture locations. The new option is benchmarked with the existing EDFM tool using synthetic and field cases.
The results of the benchmark studies indicate that high resolution LGR can minimize sensitivity to the resolution of matrix grid. Flexible DPDK framework allow us to utilize existing reservoir simulation workflow for grid property modification with clear and detailed 3D visualization of matrix and fracture through comerically available visualization packages.
The new option provides a precise and efficient method to simulate complex fracture networks. Implementation and integration with other simulation workflows are straightforward since it makes use of existing functionalities and frameworks in a commercial simulator. Potential applications to improve the efficiency of UCR factory operations include automatic probabilistic forecasting, history matching, and optimization.