bluuebunny/crossref_metadata_2025_split huggingface dataset:
A First Principles Model for Virtually Sensing Operational Parameters in an ESP Well
Authors: Aceros Egner , Camargo Edgar , Canelón José , Verde Alexander 
Published: October 2018

Abstract
The main challenges during the operation of electric submersible pumps (ESP) lifted wells include running the well at its optimal point, while honoring operational constraints posed by the production system, and extending the service life of the equipment. Overcoming these challenges will typically require building and continuously updating a model of the system. Now, due to issues such as high cost of sensors (including installation, calibration and maintenance), difficulty to reach the sensing point or lack of adequate technology, measuring some variables may be very hard or even impossible. An alternative is to develop a virtual sensor (model) to estimate unmeasured variables from measured values of other variables at different locations along the well. This work presents a model developed based on physical principles to accurately estimate key operational parameters of ESP lifted wells. The model comprises three differential equations that express the derivatives of pump flowrate, submergence level and well head pressure. Assuming as known the pump frequency, casing head pressure and production line pressure, these equations are solved numerically to estimate time profiles of submergence level, well head pressure, pump flowrate, pump intake pressure, pump discharge pressure and flowing bottomhole pressure. The model was instantiated and simulated for a particular ESP lifted well, and showed outstanding performance when estimating pump intake pressure and pump flowrate, as compared to a commercial simulator. The proposed virtual sensor exhibits high accuracy using a model with simplified equations, which can be executed quickly and reliably using few computational resources (processing time and memory); therefore, this sensor is completely suitable for direct installation in the ESP well (on a PLC or a RTU) for real-time monitoring, control and optimization. Other advantages of the proposed model include that it (i) reduces the required surface and bottomhole instrumentation, (ii) estimates the values of the variables during the transient between operating points, (iii) can be used to analyze the influence of operating parameters in the well behavior, without affecting production rate, (iv) incorporates a service factor to account for the equipment wear due to normal operation and (v) can be used in the implementation of optimization and control strategies.
Estimation and Analysis of Carbon Dioxide Friction Loss in Wellbore During Liquid/Supercritical Carbon Dioxide Fracturing
Authors: Li Xiaojiang , Li Gensheng , Sepehrnoori Kamy , Yu Wei , Wang Haizhu , Liu Qingling , Zhang Hongyuan , Chen Zhiming 
Published: October 2018

SummaryThe push to extend fracturing to arid regions is drawing attention to water-free techniques, such as liquid/supercritical carbon dioxide (CO2) fracturing. It is important to understand CO2 flow behavior and thus to estimate the friction loss accurately in CO2 fracturing, but no focus on CO2 friction loss in large-scale tubulars has been made until now. Because of the difficulty in conducting field-scale experiments, we develop a computational-fluid-dynamics (CFD) model to simulate CO2 flow in circular pipes in this paper. The realizable k-ε turbulence model is used to simulate the large-Reynolds-number fully turbulent flow. An accurate equation of state (EOS) and transport models of CO2 are used to account for CO2-properties variations with pressure and temperature. The roughness of the pipe wall also is considered. Our model is verified by comparing the simulation results with the experimental data of liquid CO2 and correlations developed for water-based fluid. It is confirmed that the friction loss of CO2 follows the phenomenological Darcy-Weisbach equation, regardless of the sensitivity of CO2 properties to pressure and temperature. The commonly used correlations also can give good predictions of the Darcy friction factor of CO2 within an acceptable tolerance of 4.5%, where the pressure range is 8 to 80 MPa, the temperature range is 250 to 400 K, the tubular-diameter range is 25.4 to 222.4 mm, and the Reynolds-number range is 105–108. Of all correlations used in this paper, the ones proposed by Colebrook and White (1937), Swamee and Jain (1976), Churchill (1977), and Haaland (1983) are recommended for field use. Finally, we investigate the influence of flowing pressure and temperature on Reynolds number, Darcy friction factor, and friction loss of CO2, and compare the difference between friction loss of water and of CO2 at different pressure, temperature, and flow-rate conditions.
Production-Performance Analysis of Composite Shale-Gas Reservoirs by the Boundary-Element Method
Authors: Wu Minglu , Ding Mingcai , Yao Jun , Li Chenfeng , Huang Zhaoqin , Xu Sinan 
Published: October 2018

Summary
A shale-gas reservoir with a multiple-fractured horizontal well (MFHW) is divided into two regions: The inner region is defined as stimulated reservoir volume (SRV), which is interconnected by the fracture network after fracturing, while the outer region is called unstimulated reservoir volume (USRV), which has not been stimulated by fracturing. Considering an arbitrary interface boundary between SRV and USRV, a composite model is presented for MFHWs in shale-gas reservoirs, which is based on multiple flow mechanisms, including adsorption/desorption, viscous flow, diffusive flow, and stress sensitivity of natural fractures. The boundary-element method (BEM) is applied to solve the production of MFHWs in shale-gas reservoirs. The accuracy of this model is validated by comparing its production solution with the result derived from an analytical method and the reservoir simulator. Furthermore, the practicability of this model is validated by matching the production history of the MFHW in a shale-gas reservoir. The result shows that the model in this work is reliable and practicable. The effects of relevant parameters on production curves are analyzed, including Langmuir volume, Langmuir pressure, hydraulic-fracture width, hydraulic-fracture permeability, natural-fracture permeability, matrix permeability, diffusion coefficient, stress-sensitivity coefficient, and the shape of the SRV. The model presented here can be used for production analysis for shale-gas-reservoir development.
A Practical Methodology for Production-Data Analysis of Single-Phase Unconventional Wells With Complex Fracture Geometry
Authors: Chen Zhiming , Liao Xinwei , Zhao Xiaoliang 
Published: October 2018

Summary
Forecasting coalbed-methane well performance in the Qinshui Basin is a key task for predicting future gas production. There is evidence suggesting that complex fracture geometry and multiple hydraulic-fracture networks might develop. Unfortunately, very limited work has been published on the production analysis of multiple-fractured vertical wells (MFVWs) in coalbed-methane reservoirs. To better understand the production performance of the MFVWs, a new, fast, and reliable methodology is presented in this paper. This semianalytical methodology is derived from an analytical reservoir solution and a numerical fracture solution. Dual-porosity, gas-diffusion, gas-adsorption, and stress-sensitivity effects are considered. Verification of the methodology is accomplished through comparison with synthetic-reservoir-simulation cases and with field-performance data. Good agreement is shown between results from the proposed methodology and those from a reservoir-simulation model. Results from this study indicate increasing transient-gas-production rate and cumulative gas recovery with increasing natural-fracture permeability, gas-storage coefficient, Langmuir volume, fracture conductivity, and fracture length. The transient gas-production rate and cumulative gas recovery were found to decrease with increasing stress-sensitivity coefficient. The parameters found to have the strongest and weakest effects on the gas-production rate were the natural-fracture permeability and the fracture conductivity, respectively. Results from this study on MFVWs in coalbed-methane reservoirs indicate fracture length is more important than fracture conductivity in terms of its effect on gas productivity.
The Effect of Voidage-Displacement Ratio on Critical Gas Saturation
Authors: Kim Tae Wook , Kovscek Anthony R. 
Published: October 2018

Summary
The critical gas saturation in permeable sands was studied as a function of depletion rate and the presence of an aqueous phase as the major experimental variables. Voidage-replacement ratios (VRR = injected volume/produced volume) less than 1 were used to obtain pressure depletion with active water injection. Three different live crude oils were considered. Two of the oils are viscous Alaskan crudes with dead-oil viscosities of 87.7 and 600 cp, whereas the third is a light crude oil with a dead-oil viscosity of 9.1 cp. The critical gas saturation for all tests ranged from 4 to 16%. These values for critical gas saturation are consistent with the finding that the gas phase displayed characteristics similar to those of a foamy oil. For a given oil and depletion rate, the critical gas saturation was somewhat larger for VRR = 0 than it was for VRR = 0.7. The oil recovery correlates with the critical gas saturation (i.e., for a given VRR, tests exhibit greater oil recovery when the critical gas saturation is elevated). For the conditions tested, there was not a strong correlation of critical gas saturation over more than two orders of magnitude of the rate of pressure depletion, for a given VRR. Such behavior might be consistent with theoretical studies reported elsewhere that suggest that the critical gas saturation is independent of the pressure-depletion rate when the rate of depletion is small.
Heavy Oil Extraction in Texas with a Novel Downhole Steam Generation Method: A Field-Scale Experiment
Authors: Hascakir Berna , Noynaert Sam , Prentice J. Andrew 
Published: October 2018

Abstract
Heavy oil extraction requires heat introduction to the reservoir to enhance the mobility of oil. While steam injection is one of the most reliable thermal EOR methods for heat introduction, it has several operational, technical, economic, and environmental limitations. This study investigates the effectiveness of a newly developed downhole steam generator which not only minimizes the heat losses due to distance the between generation and injection but accomplishes oil production with lower steam and energy requirements. A test of the downhole steam generator took place in a small 20 acre area northeast Texas with 13 wells accessing a shallow (540 feet TVD) heavy oil bearing sandstone. The viscosity and API gravity of the heavy oil was reported as 3,000 cP at 100 °F and 19 °API. The initial oil and water saturation were approximately 65% and 35% respectively.
Steam injection was started in April of 2013 at steam rates of up to 1300 bbl/day of 600°F steam, producing a total of 540 million BTU per day. The steam front was carefully monitored with temperature readings through oil sampling, both on an individual well basis. According to the temperature readings, steam front movement was faster than typical steam flooding cases in such high viscosity oil reservoirs. Preferential steam propagation occurred towards the northwest of the field due to reservoir dipping towards the southeast. The oil production increased on both the 20 acre test site and wells outside of the test site. The varying distances between injection wells and production wells enabled us to observe steam propagation at varying length. Thus, we could acquire produced oil sampling at varying steam exposure times at different locations and depths. Viscosity, density, and compositional analyses were carried out on the produced oil samples. It has been observed that the viscosity and density of produced oil were not improved due to emulsion formation which is a common concern for any steam injection project. However, further analysis revealed that emulsion breaking is possible with the use of asphaltene insoluble solvents or cationic surfactants. Since the novel design of the downhole steam generator allows injection of any additional chemical with steam during the process, these chemicals could be added to the steam stream to enhance the effective steamed area and reduce the flow assurance related problem. The new downhole steam generation tool provides an opportunity to generate steam in-situ and co-inject steam with additional chemicals to prevent emulsion formation and asphaltene precipitation. Thus, this study proves that downhole steam generation can be feasible for heavy oil extraction, even for small, low-rate fields, if all drawbacks (such as emulsion formation and asphaltene precipitation) are considered and the chemicals injected with steam are selected properly.
Data-Driven In-Situ Geomechanical Characterization in Shale Reservoirs
Authors: Li Hao , He Jiabo , Misra Siddharth 
Published: October 2018

Abstract
Compressional and shear travel time logs (DTC and DTS) acquired using sonic logging tools are crucial for subsurface geomechanical characterization. In this study, 13 ‘easy-to-acquire’ conventional logs were processed using 6 shallow learning models, namely ordinary least squares (OLS), partial least squares (PLS), elastic net (EN), LASSO, multivariate adaptive regression splines (MARS), and artificial neural network (ANN), to successfully synthesize DTC and DTS logs. Among the 6 models, ANN outperforms other models with R2 of 0.87 and 0.85 for the syntheses of DTC and DTS logs, respectively. The 6 shallow learning models are trained and tested with 8481 data points acquired from a 4240-feet depth interval of a shale reservoir in Well 1, and the trained models are deployed in Well 2 for purposes of blind testing against 2920 data points from 1460-feet depth interval. Following that, 5 clustering algorithms are applied on the 13 ‘easy-to-acquire’ logs to identify clusters and compare them with the prediction performance of the shallow learning models used for log synthesis. Dimensionality reduction algorithm is used to visualize the characteristics of the clustering algorithm. Hierarchical clustering, DBSCAN, and self-organizing map (SOM) algorithms are sensitive to outliers and did not effectively differentiate the input data into consistent clusters. Gaussian mixture model can well differentiate the various formations, but the clusters do not have a strong correlation with the prediction performance of the log-synthesis models. Clusters identified using K-means method have a strong correlation with the prediction performance of the shallow learning models. By combining the predictive shallow learning models for log synthesis with the K-means clustering algorithm, we propose a reliable workflow that can synthesize the DTC and DTS logs, as well as generate a reliability indicator for the predicted logs to help an user better understand the performance of the shallow learning models during deployment.
Predicting Sand Production in HPHT Wells in the Tarim Basin
Authors: Wang Haotian , Yang Xiangtong , Zhang Wei , Sharma Mukul M. 
Published: October 2018

Abstract
The objective of the study is to determine the main mechanisms for sand production and to propose completion designs to minimize sand production for HPHT gas wells in the Tarim Basin. Sand production has been a very serious concern in these HTHP gas wells. This paper presents field results for several key wells which are prone to sanding and investigates the possible reasons and mechanisms responsible for sand production. A fully coupled 3D, poro-elasto-plastic sand production model has been developed and applied to study sand production issues for these wells. Sand production data from several wells were analyzed to better understand the conditions under which sand production occurs and conditions under which it is mitigated.
The sand production model was used to model the different completion designs and flow back strategies that were used in the field. The model couples multi-phase fluid flow and elasto-plasticity to simulate pressure transient and rock deformation during production. The sanding criterion is a combination of both mechanical failure (shear/tensile/compressive failure) and fluid erosion. A novel cell removal algorithm has been implemented to predict the dynamic (time dependent) sand production process. In addition, the complex geometry of the wells and perforations are explicitly modeled to show cavity propagation around hole/perforations during sand production.
For this study, triaxial tests on core samples have been conducted and the stress-strain curves under different confining stresses are analyzed to obtain rock properties for both the pre-yield and post-yield period. The wells were categorized into ones that had massive sand production and ones that showed much less sand production. Operational and mechanical factors that were empirically found to result in sand production were identified. The sand production model was run to verify the role played by different factors. It is shown that completion design, rock strength and post failure behavior of the rock are key factors responsible for the observed sanding in these wells. In addition, the drawdown strategy and the associated BHP change and the extent of depletion play an important role in the sanding rate. Several strategies for minimizing sand production are suggested for these wells. These include, drawdown management, completion and perforation design. In this study, we quantitatively show for the first time that data from HPHT gas wells that suffer severe sand production problems can be modeled and analyzed quantitatively to determine the mechanisms of sand production. This allows us to make operational recommendations to minimize sanding risk in these wells.
A New Geochemical Logging Tool for Determination of Formation Chemistry and Mineralogy in both Conventional and Unconventional Reservoirs
Authors: Pemper Richard , Pereira Alex , Hou Guojing , Dolliver Darrell , Tudge Joanne , Kharrazi Jennifer , Chok Hamed , Schmid Gregory , Mekic Natasa , Blankinship Tom , Epstein Robert , Cave Tim , MacPherson Adam 
Published: October 2018

Abstract
A new geochemical logging tool has been designed and developed for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The primary elements identified by the system include aluminum, calcium, carbon, chlorine, hydrogen, iron, magnesium, oxygen, potassium, silicon, sulfur, thorium, titanium, and uranium. These elements are utilized to identify the minerals present in both conventional and unconventional formations.
Tool operation begins by emitting high energy 14 MeV neutrons into the formation from a pulsed neutron generator, and the resulting gamma rays are intercepted by a high resolution, state of the art, LaBr3(Ce) detector. In order to exclude background gamma rays and provide a clean capture spectrum, a boron coating has been placed on the housing. The 3.25-inch tool diameter makes the system easier to operate in small boreholes as well as in horizontal wells.
The extensive set of detected elements is made possible by the PNG, where high speed electronics are incorporated to accrue both capture and inelastic energy spectra. A Levenberg-Marquardt matrix inversion algorithm is employed to separate the spectra into their fundamental elemental components. Characterization of the system has been achieved through numerous measurements in more than 30 formations from a newly constructed Rock Formation Laboratory in Fort Worth, Texas as well as at the Callisto Facility in the United Kingdom. A significant number of core samples were obtained from these formations and analyzed for elemental and mineralogical composition. Extensive use of MCNP modeling was exploited for the design and characterization of the system.
The final lithological and mineralogical interpretation is guided by the elemental concentrations of the various elements, as well as the computation of intrinsic sigma. Magnesium is used to differentiate between calcite and dolomite in carbonate formations. Aluminum, iron, and potassium, in addition to silicon, provide the information required to distinguish the various clays in sand/shale formations. Sulfur is vital for the identification of both pyrite and anhydrite. Ternary plots are generated to aid in the final interpretation. To demonstrate the effectiveness of this work, log examples from the field are provided.
Permanent P&A Design - What is Good Enough?
Authors: Arild Øystein , Lohne Hans Petter , Nielsen Mariann , Moeinikia Fatemeh , Selvik Jon Tømmerås , Abrahamsen Eirik Bjorheim , Ford Eric Patrick , Mansouri Majoumerd Mohammad 
Published: October 2018

Abstract
Recently, there has been a drive towards a risk-based approach to plug & abandonment (P&A) design. To apply a risk-based approach for decision-making, i.e. to decide if a P&A design is acceptable or not, risk acceptance criteria have to be established and be approved by authorities. This paper presents the core of a risk-based approach, and then present three alternative risk acceptance criteria based on leakage risk of permanently plugged and abandoned wells.
The core elements of the risk-based approach for evaluation of the containment performance in permanently plugged and abandoned wells consist of estimating probability of leakage and associated leakage rates for any proposed P&A design. These will then have to be used to evaluate the acceptability of the design, by comparing them to some defined acceptance criteria. Different principles can be followed to define such criteria, such as being consistent by accepting risk levels which have been considered acceptable in other situations, environmental survivability or considering the cost-benefit to optimize the allocation of funds.
The approach and principles used are described and applied in the context of P&A design. Based on the specification of an actual gas producing well that was permanently plugged and abandoned on the Norwegian Continental Shelf (NCS), a synthetic case study is established. Simulations are carried out to provide estimations of the core elements of the risk-based approach, i.e. leakage rate and probability of the leakage, for the synthetic case. Three examples of risk acceptance criteria are then presented and discussed. The estimations derived from simulations for the synthetic case study are used to exemplify the strengths and weaknesses of the three acceptance criteria.