bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling the Combined Effects of Water Salinity and Polymer Rheology on the Performance of Polymer Flooding and In-Depth Gel Treatment
Authors: Khamees T. K. , Flori R. E.
Published: April 2018

Assessment of the potential of polymer flooding and gel treatment to investigate their roles of improving sweep efficiency requires an accurate modeling of polymer rheology (polymer viscosity versus shear rate) coupled with the effects of water salinity. A 3-D simulation model that represent quarter of five-spot pattern with one injector and one producer was utilized to run different scenarios using 1,000 ppm partially hydrolyzed polyacrylamide (HPAM) polymer solution with brine varying in salinities from 2,000 to ppm using UTGEL simulator. The in-situ gelation system consisted of HPAM as a polymer solution, trivalent chromium (Cr3+) as a crosslinker, and malonate ion as a delaying ligand. A unified viscosity model (UVM) developed by Delshad et al. (2008) that covers a full spectrum of Newtonian, shear-thinning, and shear-thickening behaviors was used to model the polymer rheology during polymer flooding and gel treatment and the results were compared with running the same scenarios assuming shear- thinning behavior only. Input parameters that relates the effects of salinity on both polymer viscosity and polymer adsorption were obtained. Finally, the effect of the presence of divalent cations such as Ca2+, Mg2+ in the reservoir brine were also investigated.

In this study, we demonstrated that using polymer solutions that have viscoelastic characteristic such as HPAM can indeed increase recovery more than shear-thinning behavior only, and more importantly was the effect of gel rheology on the gelation process of the gel system. Thus, oil recovery factor was always higher when considering UVM compared to shear-thinning behavior only. In addition, increasing the salinity of the injected water decreases the viscosity and increases the adsorption of polymer solution; therefore, the higher the brine salinity, the lower the recovery factor. A further enhancement of the recovery factor was achieved using low-salinity chase water flooding. This improvement was more noticeable when the initial salinity of the model was very high (i.e., 20,000 ppm). In addition, the effects of lowering chase water salinity were more pronounced with polymer flooding compared to gel treatment. Moreover, the treatments were less efficient when the hardness was high in the reservoir brine. Finally, low-salinity chase water flooding reverse the effect of the presence of divalent cations in the reservoir brine.
An Integrated Framework of Stress Inversion and Coupled Flow and Geomechanical Simulation for 4D Stress Mapping
Authors: Bubshait A. A. , Aminzadeh F. , Jha B.
Published: April 2018

A change in pore pressure due to production/injection causes changes in both the total stress and the effective stress in the reservoir. These stress changes, when projected onto a fault, may induce fault failure and seismicity depending on the fault rheology and friction parameters. A seismic event can be characterized by the moment tensor and the focal mechanism, which are related to the change in stress tensor causing the event. The objective of this paper is to use the theories of poroelasticity and stress inversion to develop a framework for mapping spatiotemporal changes in reservoir stresses caused by injection and production processes. We use a poro-elastoplastic simulation approach in CMG STARS to examine stress changes resulting from production in a reservoir with a normal fault. Production-induced increase in the von Mises stress and the effective mean compression cause plastic failure within the fault. We model the shear slip as a function of the plastic strain and compute the moment magnitudes of equivalent microseismic events. The focal mechanisms of these events are used in MSATSI, a MATLAB Package for Stress Inversion, to obtain the magnitudes and directions of three principal stresses. The stress inversion algorithm is modified to calibrate the principal stresses with the stress solution from the poro-elastoplastic simulator. We find that as production continues in the reservoir, the magnitudes and directions of stresses evolve in time. The result is a framework that provides a 4D (time-lapse) stress map of a reservoir while honoring both the production/injection and microseismic data.
Reservoir Geostatistical Estimation of Imprecise Information Using Fuzzy Kriging Approach
Authors: Zhao X. , Popa A. S. , Ershaghi I. , Aminzadeh F. , Li Y. , Cassidy S. D.
Published: April 2018

This paper presents a methodology for geostatistical estimation of reservoir properties to handle uncertainties in observation and modeling. Given certain known data in a geological region, the Kriging methodology is used to estimate or predict spatial phenomenon at non-sampled locations from the estimated random function. The approach assumes that the data is accurate and precise and the random function is generated from a thorough descriptive analysis of the known dataset. Regarding the assumptions considered in classic Kriging, it is realistic to assume that spatial data contains a certain amount of imprecision mostly due to measurement errors, and the information is lacking to properly assess a unique random function model. This paper presents a methodology for geostatistical estimation of reservoir properties to handle uncertainties in observation and modeling. Combination of regular or classic Kriging and Fuzzy Logic method is proposed. As such, imprecise variogram parameters are modeled based on Fuzzy Logic theory, while the predictions and variances are computed from Kriging analysis characterized by membership functions. Lastly, an optimization method is included to solve the constrained fuzzy non-linear equation system. The proposed methodology was implemented into a friendly integrated tool, which enables the user to create a preferred grid, conduct statistical analysis and run fuzzy kriging for various problems. The tool was validated using the SPE-10 porosity data. Additionally, a case study has been conducted using measured core permeability data in a heterogeneous reservoir to demonstrate the viability of the technology.
An Experimental Investigation of WAG Injection Performance under Near-Miscible Conditions in Carbonate Rock and Comparison with Sandstone
Authors: Alkhazmi Bashir , Farzaneh S. Amir , Sohrabi Mehran , Sisson Adam
Published: April 2018

In this study, the effect of rock type on two-phase and three-phase flow and displacements have been experimentally investigated as a part of a study on the performance of WAG injection in sandstone and carbonate rocks. A series of core flood experiments have been performed under reservoir conditions to investigate the effect of parameters pertinent to the performance of WAG injection. Clashach sandstone and Indiana limestone cores with almost similar porosity and permeability were selected for this work. To reduce the effects of experimental artifacts, large cores were used with diameter and length of 2 in × 2 ft respectively. To investigate the role of rock type, the WAG design parameters including injection order, injection strategy, and slug size were kept unchanged for the sandstone and carbonate rocks. Both core flood experiments were performed on water-wet cores and at near-miscible gas/oil IFT conditions.

Comparison of our core flood experiments reveal that even though the waterflood efficiency was higher in carbonate core than in sandstone rock, the overall oil recovery performance by the alternation of water and gas injections in the sandstone rock outperformed its trend in the carbonate core. Ultimate oil recovery values of 88.35 % (IOIP %) and 71.0 % (IOIP %) were obtained for the sandstone and the carbonate cores, respectively. The results show that about 39.12 % (IOIP %) and 12.37 % (IOIP %) of additional oil was recovered by the alternation of water and gas injection in the sandstone and carbonate cores, respectively. Comparing the average saturation profiles in the cores revealed that the higher trapped gas saturation in sandstone rock had significantly enhanced its oil recovery performance, during the tertiary water and gas injections, compared with that in the carbonate rock. The results also revealed the impact of rock type on pressure drop and fluid saturation distribution.
Geomechanical Impact on Gas Recovery from Marcellus Shale
Authors: El Sgher Mohamed , Aminian Kashy , Ameri Samuel
Published: April 2018

The production rate from unconventional reservoirs declines more rapidly than conventional reservoirs. The production from the reservoir result in an increases in the net stress due to reduction in the pore pressure while the overburden pressure remains constant. This leads to formation permeability reduction, both for the matrix and the fissures, as well as and conductivity impairment in hydraulic fracures due to proppant embedment. Information relative to the impact of stress (geomechanical) on matrix permeability and porosity, hydraulic fracture conductivity, fissure permeability were obtained from published studies. The effects of stress on the matrix, and fissure permeability, and propped fracture conductivity were then incorporated into the numerical reservoir simulator to predict production performance.

The objective of this study is to investigate the impact of the net stress changes on gas production from the horizontal wells with multiple hydraulic fractures completed in Marcellus Shale. A commercial reservoir simulator was used to develop the base model for Marcellus shale horizontal wells. The model incorporated various storage and production mechanisms inherent in shales, i.e., matrix, natural fracture, and gas adsorption as well as the hydraulic fracture properties. The core, log, completion, stimulation, and production data from wells located at the Marcellus Shale Energy and Environment Laboratory (MSEEL) were utilized to generate the formation and completion properties for the model. MSEEL is a Marcellus Shale dedicated field laboratory and a research collaboration between West Virginia University, Ohio State University, The National Energy Technology Laboratory, and Northeast Natural Energy. Shale petrophysical properties at this site were determined by Precision laboratory equipment. These laboratory measurments provided the impact of net stress on core plug permeability and porosity. Furthermore, these experimental results were utilized to determine the the fissure closure stress. The relation between the propped fracture conductivity with the net stress were obtained from published studies on cores plugs collected from Marcellus shale. The production data from two horizontal wells at MSEEL site, were utilized for history matching with the model first by inluding geomechanical effects and then by exdcluding them. This approach allowed the impacts of stress-dependent matrix permeability, fissure permeability, and hydraulic fracture conductivity on the gas production to be evaluated. The base model was finally used to perform a number of parametric studies. The inclusion of geomechanical effects in the model improved the model predictions particularly at the early stages of the production. The results indicated that fissure permeability reduction due to stress, compared to reduction in matrix permeability and propped fracture conductivity, has more impact on gas production when the pressure in the vicinity of the well has declined.
Asphaltenes Contribution in Emulsion Formation During Solvent-Steam Processes
Authors: Ng A. , Ovalles C. , Benson I. P. , Hascakir B.
Published: April 2018

The objective of this paper is to enhance the produced oil quality during solvent-steam flooding processes by using asphaltenes precipitants and environmentally friendly solvents as injection fluid. This way, it is aimed to increase the asphaltene deposition tendency and decrease the emulsion formation severity.

Eight one-dimensional core flood experiments were conducted; one steam flooding, three solvent flooding, and four solvent-steam flooding. Five different solvents were tested; propane, n-hexane, toluene, Benzoyl peroxide (BP), and a plant-based environmentally friendly solvent (MS). Solvent and water injection, oil and water production, and temperature along the core flood were continuously measured during each experiment. Both produced oil and residual oil samples were further analyzed to investigate the quality of produced oil samples and the amount of asphaltenes deposited on spent rock. An ASTM method which uses n-pentane was implemented to separate asphaltenes from both produced and residual oil samples. The water content of produced and residual oil samples was determined through thermogravimetric analysis (TGA) and the water-in-oil emulsion content of produced oil samples was visualized with an optical microscope. To understand the impact of each SARA (Saturates, Aromatics, Resins, and Asphaltenes) fractions on produced oil quality during solvent-steam processes, every fraction was exposed to liquid or vapor water and examined under a microscope.

It has been observed that stability of asphaltenes and emulsions varies in the presence of vapor or liquid water. Aromatics and Resins fractions are the main contributors of water-in-oil emulsion formation, and emulsion formation is enhanced with the addition of asphaltenes. Vapor-water (steam) promotes the formation of more severe emulsions than liquid-water. Hence, the emulsion formation mechanism was predicted to start with a foam-formation step in where the vapor steam diffuses into the liquid crude before condensing to form liquid water droplets, and then, forming an emulsion at lower temperatures. Since asphaltenes insoluble solvents were used, diffusion of steam occurs mostly in deasphalted oil and mainly in aromatics and resins.
Impact of Thermal Maturation on Wave Velocity in the Bakken Shale
Authors: Kong L. , Ostadhassan M. O. , Sarout J. , Ling K. , Li C. , Wang H.
Published: April 2018

Thermal maturation not only affect the geochemical properties of Bakken shale but also impact the geomechanical properties of organic rich shale formations to some extent. In this study, kerogen was modeled as a function of thermal maturation based on differential effective medium theory. Four shale samples were collected and tested by X-ray diffraction(XRD) and Rock Eval to analyze the mineralogy and geochemical properties. Hudson’s model was used to simulate the acoustic properties of Bakken shale affected by the thermal maturity. The result shows an apparent trend between vitrinite reflectance (Ro) with compressional and shear wave velocity. As the Ro increases, the wave velocity decreases due to the kerogen maturation. Especially during certain interval, the decreasing is significant. This study proves caution should be taken when inverting the seismic or logging data to elastic properties of Bakken shale. As this is a theoretical model, more factors should be integrated to have a more accurate result in the future.
Impact of Shrinking Fracture Length and Decreasing Fracture Conductivity on Bottom-Hole Pressure Performance: A Semi-Analytical Model to Characterize Waterflood-Induced Fracture Around Water Injection Well
Authors: Wang Y. , Cheng S. , Zhang K. , Ayala H. L. F. , Qin J. , He Y.
Published: April 2018

There is growing evidence showing that water injection may induce formation fracturing around injectors in tight reservoirs. Because waterflood-induced fractures (WIFs) are not strengthed by proppants, they close gradually during the field-testing period, which results in "fracture-closure-induced" flow rate, shrinking fracture length (SFL) and decreasing fracture conductivity (DFC). In this paper, we propose a novel semi-analytical model to characterize the BHP behavior of water injectors under the influence of WIF. We consider that pressure losses take place within three sections: reservoir, WIF and wellbore. Flows between reservoir and WIF are linked through a fracture-storage coefficient and fracture-face skin factor, while flows between WIF and wellbore are coupled via wellbore-storage coefficient and choked-fracture skin factor. Finite difference and perturbation theory methods are deployed to include the SFL and DFC effects, respectively. Duhamel principle is invoked to characterize flow rate changes caused by wellbore and fracture storage effects. Results show that bi-storage effects can be identified as two unit slopes in the pressure derivative curve. In the abscense of extra pressure drop between wellbore and WIF, i.e., choked-fracture skin equals to zero, a prolonged storage period with a considerably large storage coefficient can be obtained. In addition, we find that SFL could cause the variable fracture storage effect while DFC may lead to the upward of pressure derivative curve at late times. Finally, the model is successfully applied in the Changqing Oilfield to validate its reliability.
Optimization of CO2-Foam Injection through Resistivity and Pressure Measurements
Authors: Karakas M. , Aminzadeh F.
Published: April 2018

This paper focuses on the use of combined resistivity and pressure measurements to determine the effectiveness of foam as a mobility control method and presents a theoretical framework to describe the expected resistivity changes during CO2-Foam displacements. With this objective, we first provide equations to estimate the resistivity for CO2-Foam systems and then utilize Population Based (PBE) and Steady-State Foam models to quantify these effects. Using analytical solutions based on the fractional flow theory, we present the corresponding resistivity and mobility distributions for both ideal and non-ideal reservoir displacement scenarios. Additionally, assuming pressure measurements only, we examine the inter-dependency between various foam parameters. Our results suggest that combination of Pressure and Resistivity measurements in time-lapse mode could be deployed as an effective monitoring tool in field applications of the (CO2) Foam processes. The proposed method is novel as it could be employed to predict under-performing CO2-Foam floods as well as improve oil recovery and CO2 storage.
A Pulsed Neutron Comparison Between an Open and Casedhole Well: An Alaskan Case Study
Authors: Burt J. , Zhou T. , Rose D. A. , Grover R. , Ahmad S. , Nemec J. , Dunston J.
Published: April 2018

The latest pulsed neutron spectroscopy tool for logging behind casing provides for enhanced formation evaluation due to improved self-compensated sigma and porosity measurements and a new measurement, the fast neutron cross section (FNXS), which is independent of the formation hydrogen index (HI). The FNXS is highly sensitive to gas filled porosity and can be used to differentiate between gas-filled and low-porosity zones, which was previously not possible. The FNXS measures the ability of the formation to interact with fast neutrons which is highly dependent on atomic density and not dominated by any particular isotopes, in contrast to traditional sigma and porosity measurements.

This paper examines and compares the results of gas identification and lithology identification using pulsed neutron spectroscopy in an open-hole and a cased-hole environment. Most pulsed neutron tools are run after casing; this study provides a unique example to compare the effect of casing on the spectroscopy by comparing the cased hole measurements to measurements taken in the open hole, before the casing was run.
Novel Observations of Salt Front Behaviour in Low Salinity Water Flooding
Authors: Al-Ibadi H. H. , Stephen K. D. , Mackay E.
Published: April 2018

The conventional method for describing transport of solutes such as salt, polymer and tracers is to use the mass conservation law. In simulation of this law for Low Salinity Water Flooding (LSWF), the effective salinity range defines how salt affects the mobility of water and appears to be crucial for controlling fluid movement. In this study, we examined the non-linear feedback between salt concentration movement and the low salinity water front as a function of physical and numerical dispersion, in combination with the effective salinity range, and we investigated how the front speeds were altered.

We examined a numerical model of the mass conservation law to simulate LSWF at the reservoir scale. The cell sizes and the time steps were chosen to control the numerical dispersion coefficient in place of physical diffusion. A range of diffusion coefficients was considered along with various representations of the effective salinity range and the function that controls the effect that salt has mobility. The latter has been shown to be variable in the literature. We compared simulations to the analytical solution of solute transport obtained for the diffusion-advection equation assuming a fixed flowing velocity.

We observed that the salinity front moved faster than was predicted by the analytical solution and this effect was increased the further the effective salinity range was set below the connate water salinity. In this case, the higher salt concentrations lay in the faster moving water (the connate water front), which also speeded up. This was very much a dispersion related effect, with the variation of velocity growing as the salt concentration spread out. By implementing many numerical tests, we obtained a modification to the advection term in the conventional mass conservation law of solute transport. This term depends on the Peclet number, the velocities of the high and low salinity fronts and the effective salinity as a proportion to the connate water salinity. In an advection-diffusion system, these factors usually affect only the advection term (the front velocity), while the diffusion term is unchanged.

From numerical tests, we can now rapidly predict the movement of the salt front by this newly derived modification of the analytical solution.
Engineered Completion and Well Spacing Optimization Using a Geologically and Geomechanically Constrained 3D Planar Frac Simulator and Fast Marching Method: Application to Eagle Ford
Authors: Paryani M. , Bachir A. , Smaoui R. , Umholtz N. , Khodabakhshnejad A. , Ouenes A.
Published: April 2018

Optimizing a well's hydraulic fracture design within a pad development environment is a multi-disciplinary effort and requires a 4-dimensional understanding of the reservoir. This paper presents a workflow that uses an integrated workflow that combines geology, and geomechanics to build a reservoir model which can be interrogated and updated with a geologically and geomechanically constrained grid-based 3D planar frac model and production simulation using a fast marching method. In this case, as applied to an Eagle Ford well to address concerns of completion optimization, production and depletion forecasting, well spacing and well interference.

The workflow captures the variability of stresses and rock properties along the wellbore and around it by using multiple geologic and geomechanical approaches. The estimated variability of rock mechanical properties is used as input in a 3D planar frac simulator. An alternative approach to geoengineering a completion, using the differential stress derived from geomechanical simulation that overcomes the limitations of well centric methods, is also illustrated.

The frac design results are used as inputs/constraints in a new reservoir simulator that was developed using the Fast Marching Method to estimate drainage area. This allows for a constrained, yet extremely fast estimate of the EUR and resulting pressure depletion, addressing the important concerns of well spacing optimization and prevention of frac hits and well interferences, all in a timely manner.

The integrated approach facilitates adaptive frac design which honors in-situ conditions including stress field heterogeneity, stress shadow effects and the pressure depletion from nearby producing wells. The proposed workflow enables greater investment efficiency and promotes field development optimization.
Optimization of Horizontal Wellbore Trajectory and Placement of Hydraulic Fracturing Stages in Tight Heterogeneous Gas Condensate Reservoirs Using Derivative Free Algorithms
Authors: Olusola B. , Aguilera R.
Published: April 2018

We present hybrid derivative free algorithm methods that maximize NPV while solving the problem of placement of hydraulic fracturing stages and horizontal wellbore trajectory in a tight heterogeneous gas condensate reservoir. These parameters are important in reservoir management and field development optimization as they determine the interaction of the wellbore with the reservoir. Thus, they have a large impact on production performance of the field and the cost of field development.

We couple a tight heterogeneous gas condensate reservoir model to an optimization algorithm that determines the parameters that maximize the economic value of the field. The optimization algorithm proposed in this paper exploits the advantage of stochastic global search (particle swarm optimization) and local pattern search (hill climber) techniques to find the optimized parameters. The optimization process starts with the particle swarm optimization (PSO) algorithm, which is executed with an initial guess based on engineering experience until the objective function (in this study NPV) fails to improve in the next couple of iterations. This is followed by the hill climber (HC) algorithm that improves the objective function.

Observations from our investigation show that an optimal field development plan (FDP) is essential to optimize the placement of hydraulic fracturing stages along a horizontal wellbore and to optimize the wellbore trajectory inside the reservoir. However, these parameters would have to be optimized simultaneously in a non-systematic manner. We integrate reservoir engineering experience and economics knowledge into the optimization algorithm by embedding practical constraints into the problem formulation.

The algorithm is executed in a reasonable amount of computation time, considering the complexity of the problem. The optimization process evaluates various possible field development plans involving different hydraulic fracturing stages and well placement trajectories. The investigation demonstrates how these parameters impact the economic value of the field, how to optimize the placement of hydraulic fracture stages along a horizontal wellbore, and how to optimize the wellbore trajectory inside the reservoir.

The methodology presented in this work should allow industry professionals working with unconventional reservoirs to improve the economic value of a field in a shorter timeframe while considering all possible field development plans, a task that would be time consuming and tedious if carried out manually.
Performance Analysis of a Novel Heavy Oil Recovery Process Using In-Situ Steam Generated by Thermochemicals
Authors: Moussa T. M. , Patil S. , Mahmoud M. A.
Published: April 2018

Heavy oil has attracted global attention due to its huge volume of original oil in place. However, there are numerous operation and economic challenges during the recovery of heavy oil due to its high-viscosity and high-density. Thermal recovery methods such as steam injection is viable and commonly used to recover heavy oil and bitumen primarily by thermally altering oil viscosity and improving the displacement of heavy oil. However, there are significant heat losses before the steam reaches the heavy oil, in addition to the concerns of high cost and emission of greenhouse gases. One of the promising new heavy oil recovery approaches is generating steam, in-situ, using chemical reaction to reduce the oil viscosity, improve the mobility ratio, and enhance the heavy oil displacement.

The objective of this work is to introduce a novel heavy oil recovery process using in-situ steam generated by thermal and chemical reaction and analyze its recovery performance compared with conventional steam injection method from the economic point of view, as well as based on the achieved net present value (NPV) of each technique. Sensitivity analysis of the proposed recovery processes to different operational parameters is introduced. The CMG STARS™ Simulator is used in this work to simulate reservoir models with different operational parameters. The recovery performance of the proposed technique outperformed the conventional steam flooding method and achieved higher NPV after ten years of production.

This is the first time to use NPV and consider all economic parameters to analyze the performance of the developed recovery process of in-situ steam generation by chemical reaction. This research shows that the recovery of the proposed method is economic, and applicable to the reservoirs which are not viable for conventional steam flooding methods and it is a step forward to eliminate CO2 emissions associated with thermal recovery processes.
Recovery Improvement by Chemical Additives to Steam Injection: Identifying Underlying Mechanisms Through Core and Visual Experiments
Authors: Bruns F. A. , Babadagli T.
Published: April 2018

Steam injection of any kind (flooding, cyclic, or gravity drainage) is a proven heavy-oil recovery method; however, it also involves excessive costs due energy and water needed for steam generation. Any effort in reducing this cost or improving oil recovery is essential for sustainable production, especially in times of low oil prices. Chemical additives to steam were suggested a few decades ago to improve two major mechanisms, namely heat transfer and interfacial phenomena, but research in that area discontinued due to the cost and thermal stability problem of the additive chemicals. With recent advancements in nano-technologies, new generation chemicals showed potential to reconsider chemical additives to improve the efficiency of steam injection. This, however, requires extensive research especially for mechanism identification. The objective of this paper is to identify the flow characteristics and the mechanisms involved in recovery enhancement by chemical additives through core and visual tests.

To mimic the gravity assisted drainage and flooding type steam displacement tests we performed previously (Bruns and Babadagli 2017) on cores saturated with 27,000 heavy-crude-oil, a visual Hele-Shaw model was designed to simulate the same process and identify the physical characteristics of the steam-condensate-oil interface and the role played by added chemicals. Majority of the chemicals/chemical blends showed either improvement in the rate or ultimate recoveries in the coreflooding tests and, based on this data, the best performing and the most thermally stable chemicals were selected for the visual tests. These chemicals include ionic liquids, internal olefin sulfonate, biodiesel (thermally stable surface active agents) and solvents (heptane), and nano-fluids (silicon oxide). The chemical solution was injected at constant rate and pressure after being vaporized in an oven along with steam and the whole process was recorded with a camera.

The contribution to recovery improvement through these phenomena in flooding and gravity controlled cases were identified. Foaming, emulsification, and IFT reduction yielding reduced drag forces between two phases at the interface were observed to be the main reason for positive contribution of chemicals. Biodiesel (Surfactant 1) exhibited a diffusion-like behavior near the injection port where no residual oil was noticed. The solvent (heptane), simulating ES-SAGD, stabilized the flow of steam in the late stage of the experiment due to the viscosity reduction. Improved oil + condensate drainage was assumed to be the contributing mechanism because of the change in surface properties during the injection of the ionic liquid. Nanoparticle, silicon oxide, and the internal olefin sulfonate (Surfactant 2) showed similar improvements in tip-splitting of the displacing fingers. It was concluded that the interfacial tension (IFT) reduction resulted in a wider occupation of the Hele-Shaw cell (better lateral sweep).
Extra Heavy Oil Production Using Dilution: Viscosity Measurement and Modeling
Authors: Alboudwarej H. , Mohan J. , Gozalpour F. , Jarvis S. S.
Published: April 2018

A viable method to produce a deep extra heavy oil reservoir with an in-situ viscosity in excess of 1000 cp is viscosity reduction with dilution, and where steam flooding may be an unlikely option. The objective of this study is to determine viscosity reduction of an extra heavy oil sample as a function of pressure, temperature and composition, where composition refers to addition of different amounts of diluents. Results of this study and modeling of the mixture viscosity can be used to guide future operational decision making to develop large heavy oil resources, where steam flood is not economical.

An extensive experimental test matrix was carried out in this study. A high-pressure capillary tube viscometer was used for viscosity measurements, which is the preferred measurement method for extra heavy oil systems. Potential compatibility issues such as wax and asphaltene formation due to changes in composition and/or temperature were considered during the design and execution of experimental work. In excess of 90 viscosity data points were measured for mixtures of an extra heavy oil sample and two diluents (a diesel sample and a light crude oil sample). The system pressure varied up to 4000 psia, the temperature varied in the range of 80-200 °F, and amount of diluents changed up to 40% by volume. Data QC protocols were implemented and quality of measured viscosities were assessed. Some measurements were repeated to ensure high quality of generated viscosity data.

Three to four orders of magnitude of viscosity reduction were observed with changes in pressure, temperature and composition. On average and for studied fluid systems, every 50 °F change, or 20% increase by volume in diluent concentration, reduced the mixture viscosity by almost an order of magnitude. The impact was less significant at higher temperatures and concentration of diluents. Viscosity data were used to develop specific mixture viscosity correlations for the systems of interest, representing measured viscosities with an average absolute deviation (AAD) of less than 3%. Furthermore, a large number of viscosity mixing rules were evaluated to represent measured viscosity data in this study. Some mixing rules predicted the viscosity data with 15-20 % deviation and an average standard deviation of 14%. A new mixing rule (Modified Ratcliff & Khan) was developed with an AAD of 11% and a standard deviation of 5% (at least 50% improvement in the performance).

Currently, universal viscosity mixing rules are not available, particularly for extra heavy oil and diluent mixtures. The novelty of this study is to provide a high-quality database of heavy oil and diluent viscosity data, together with the development of a new general mixing rule applicable to the type of oils and diluents investigated in this study.
Quantification of Gas Exsolution and Mass Transfer of Foamy Oil in Bulk Phase under Solution Gas Drive Conditions
Authors: Shi Yu , Yang Daoyong
Published: April 2018

The in-situ formation of foamy oil has been found to be a crucial mechanism accounting for the better-than-expected production performance in heavy oil reservoirs under solution gas drive. To date, the physical laws dominating gas exsolution in foamy oil have not yet been well understood, while the generation of foamy oil is essentially arose from such an extremely complicated dynamic process. In this study, a novel and pragmatic technique has been proposed and validated to quantify the gas exsolution in bulk foamy oil under solution gas drive conditions by taking into account the gas bubble size distribution and the preferential mass transfer of each gas component. Experimentally, constant-composition expansion (CCE) tests with various constant-pressure decline rates are utilized to describe the gas exsolution behaviour of alkane solvent(s)-CO2-heavy oil systems under nonequilibrium conditions, during which not only pressure and volume are simultaneously monitored and measured, but also gas samples were respectively collected at the beginning and the end of experiments to perform compositional analysis. Theoretically, a mathematical model has been formulated to quantify gas exsolution process and the preferential mass transfer between of each gas component and liquid phase in alkane solvent(s)-CO2-heavy oil systems under nonequilibrium conditions. More specifically, quasi-equilibrium boundary conditions, real gas equation and Rayleigh distribution function are combined with classical equation of motion, continuity equation, and mass transfer equation to form a novel equation matrix for quantifying gas bubble growth in foamy oil. With consideration of gas bubble size distribution and preferential diffusion of each component in a gas mixture, the total number of gas bubbles and individual diffusion coefficient of each gas component are determined by minimizing the deviation between the measured volume of alkane solvent(s)-CO2-heavy oil systems and the calculated one. More importantly, the dynamic composition of gas phase and the amounts of both entrained gas and evolved gas also can be obtained simultaneously during the gas exsolution processes. Excellent agreements between the experimentally measured parameters (i.e., volume of foamy oil, composition of evolved gas, and volume of free gas) and the calculated ones have been respectively achieved. Compared with the individual diffusion coefficient for each component in a gas mixture determined under the traditional conditions, a relatively large value has been found during mass transfer processes in a supersaturated oleic phase. Also, pseudo-bubblepoint pressure and rate of gas exsolution is found to be two mechanisms dominating the volume-growth rate of the evolved gas.
Detecting Failures and Optimizing Performance in Artificial Lift Using Machine Learning Models
Authors: Pennel Mike , Hsiung Jeffrey , Putcha V. B.
Published: April 2018

This paper will review the different types of artificial lift problems that have been diagnosed and predicted using machine learning algorithms including tubing and pump failure along with suboptimal performance of sucker rod pumps and and gas injection. The discussion will review the suboptimal performance periods that can be diagnosed and the associated impact on well performance. The presentation will focus on artificial lift and specifically on sucker rod pumps and gas lift.

The machine learning models were trained using production data for over 1 year from operating wells in the Bakken. Time series sensor and controller data for 800 wells was loaded into an AWS cloud platform for analysis and profiling. Experts in each lift type reviewed failure and performance data and identified periods of failure modes and sub-optimal performance. These events were used to train different types of machine learning and artificial intelligence algorithms include random forest, gradient boosted tree and neural network models. These models were used to diagnose and predict the problem states. The overall performance of the models was analyzed to rank and assess performance of each model, lift type and problem state.

Data science, machine learning and artificial intelligence are revolutionizing industries by applying massive low-cost computing power to optimize machine performance. Artificial lift is a good use case given the increasing number of sensors and signals being produced by the latest controllers, the improving data connectivity, lower cost of compute and data storage and the complexity of the surface and downhole problems in unconventional wells. The tubing and pump failure models proved to be highly accurate with diagnostic model accuracy > 99% and precision ranging from 50% to 60%. The long-term tubing failure model performance achieved an expected estimation error of just 31 days on a range of asset lifespans from 100 to 600 days. Suboptimal performance models had accuracy > 90%. The model performance enables high confidence interaction with the wells to react more quickly to problem states and thereby reduce downtime and improve pump effectiveness.

One of the key challenges in deploying data science in the field is to facilitate cooperation between engineers, operators and data scientists. Most of the advanced models used in other industries are based on data from on-line systems (e.g. Google, Facebook) with consistent data and defined outcomes. The oil field has unique data and environmental challenges. This paper discusses how experts in the artificial lift interacted with data scientists to understand this dynamic operating environment, the challenges with data quality and how these assets operate in the field.
Engaging and Educating our Community: A Case History of the California Regulatory Environment and a Local O&G Company's Path on Building an Ambassador Program to Empower its Employees
Authors: Lal T.
Published: April 2018

This paper focuses on California's regulatory environment and our role as industry, individuals, and the general public, in shaping its future. It provides a historical context of regulations, the current focus areas, and challenges moving forward. Improving our understanding of the energy industry empowers us to collaborate in shaping the future of California. The sustainability of the industry is important to the sustainability of the state - from families to small businesses to large employers.

Since the Industrial Revolution, energy has been the backbone of human society. Medicine, agriculture, science, technology and more are all sustained by energy. Energy demand is categorized broadly as electricity and transportation demand. Oil is the major energy source for transportation, due to availability, reliability, and economics. In the U.S., roughly 50% of the oil consumed is imported (EIA 2017). In California, the number is closer to 67% (Californians for Energy Independence 2015). One reason for high oil imports is the challenging regulatory environment.

Traditionally, the Oil and Gas (O&G) industry has relied on classic lobbying-based negotiations with agencies. However, with increasingly, widespread misunderstanding of the industry and an ever-changing landscape, it is crucial to incorporate a "boots on the ground" approach. Stakeholder engagement is key in responding to and exposing misleading tactics and messages of some industry critics.

Aera Energy LLC (Aera) has been a leader in implementing an Ambassador Program, an education program focused on providing employees an opportunity to share simple, straightforward, and accurate messages with their families and local community. With safety and environmental responsibility as the foundation for all activities, it is the "Aera Way" of doing business. We hope you are interested to learn more and see how you can be an industry Ambassador within your local community!
Integrated Stratigraphic Controls for Flow Simulation of the Wall Creek Member in the Frontier Formation: Western Powder River Basin, Wyoming
Authors: Le T. T. , Hoffman T. , LaFontaine N. , Hofmann M.
Published: April 2018

The Frontier Formation in the Powder River Basin has been re-discovered for oil and gas potential with the development of long horizontal wells and multi-stage hydraulic fracturing. Over the last decade, the Wall Creek member (WCM) of the Frontier formation has proven to be a successful hydrocarbon-producing target, yet a full understanding of the flow behavior of this complex stratigraphic unit has not been fully achieved.

The fluid and rock properties have uncertainty and are not well defined due to the low permeability rocks. This study aims to describe the fluid flow behaviors of these features and create an outcrop model that includes all the reservoir properties and geologic features to better understand hydrocarbon recovery. This project consists of two distinct aspects: (1) defining the reservoir properties through a well flow model and (2) upscaling the permeability of the reservoir models with different geologic features into an outcrop model for the WCM.

A single horizontal well flow simulation model was created to estimate the reservoir properties. Using three offset well logs, a 32 feet interval was selected to represent the net pay zone of the Wall Creek. The porosity was estimated using well logs, and permeability was established by applying a correlation of porosity and permeability found from core data. The historical production data was matched by modifying the initial fluid saturations and the rock physics parameters such as relative permeability and capillary pressure. As a result, representative fluid and rock physics models were obtained for the outcrop model.

From the outcrop study, defined geologic models with different facies of Wall Creek member were created to include abundances and orientations of mud drapes as the most impacted features that may affect the the fluid flow ability. An outcrop model captures fine heterogeneities of all the facies using flow-based upscaling of the geologic models. The effective directional permeabilities of each facies were obtained to integrate into an outcrop model to capture the geologic features that may have a large impact on the hydrocarbon recovery.

In this work, we developed methods to incorporate fine-scale (cm) geologic observations from the outcrop with well scale properties from the field in an integrated study that was ultimately used to help determine field level decisions such as well spacing and fracture spacing.
Data-Driven Production Forecasting of Unconventional Wells with Apache Spark
Authors: Mohammadmoradi Peyman , Moradi Hessam M. , Kantzas Apostolos
Published: April 2018

Real-time decision making, field surveillance, and production optimization improve the performance of existing operations to increase hydrocarbon recovery and reduce emissions. In this regard, the oil and condensate flow metering in offshore gas condensate platforms is always confronted by environmental, economic, and operational challenges resulting in uncertain production management plans. Although production forecasting of unconventional gas condensate systems is more challenging than for conventional wells, it is of great interest to support decisions by knowing the future of the wells as far as possible. The virtual flow metering techniques make it possible to utilize daily production data sets and extract information on how wells and reservoir will respond to different operational conditions. The objective of this study is to embed artificial intelligence algorithms in reservoir uncertainty modeling and present a mechanistically-supported data-driven model applicable for production forecasting of gas condensate wells with higher confidence. The outcome entails a new set of mathematical models, implemented using Apache Spark cluster computing engine with APIs in Python, that enables rigorous and robust optimization of the recovery process, designing and discovering hidden patterns in production data, and extracting reservoir information indirectly in seconds. The observations used to demonstrate the performance of the proposed hybrid model include 1600 well-testing data points together with 420 days of production history of an offshore gas condensate platform. The daily platform production is allocated efficiently to individual wells using a multilayer perceptron neural network model adaptively trained with well-testing and daily production datasets, and supported by the Energy and mass balance equations.