bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Petroleum Sensitive Countries Economic Reforms in Reaction to Fluctuating Oil Prices
Authors: Belhaj Hadi A. , Suboyin Abhijit , Ali Sawsan A. 
Published: October 2018

Abstract
Since the early 1970s, the world has witnessed fluctuating oil and gas prices with deceleration in estimated growth and production. Multiple studies have reported how economic cycles are coupled with this phenomenon and how it has influenced the world economy.
This paper provides an in-depth investigation of the various reforms and corrective measures taken by Petroleum Sensitive Countries (PSC), particularly, the United States of America, Saudi Arabia, United Arab Emirates, Russia, China, Malaysia and Indonesia. Multiple qualitative assessment of the reforms has been performed in addition to defining and assigning impact factors for their significance and probability of success. The cited reforms were, primarily, imposed to tackle the various complications resulted from low oil prices and was assumed to readjust and sustain the economy along with assisting these countries through the evident economic crunch and budget deficits with minimal damage. These highlighted reforms are analysed in depth which is followed by performing multiple comparative qualitative risk/opportunity assessments where weights have been assigned for each of the impact along with the probability of success for each type of reform.
It is found that the most common and effective reform that has been implemented by these PSCs is maneuvering with the energy prices in these countries along with production manipulation. In other words, revising energy prices and abolishing fuel subsidies for the end users, imposing taxes on commodities and limiting the total production output. From this study, it is also found that the energy prices adjustments and subsidies removal reforms has been identified as the most efficient governmental reforms fostering long term sustainability and profitability. This provides the PSCs with more opportunities to decouple their dependency on oil resources alone. Furthermore, other reforms taken by PSCs are analyzed, evaluated and compared to their respective short and long-term efficiencies followed by identifying optimum strategic reforms using multiple qualitative and comparative criterions. Reforms by Russia have also been analyzed in depth along with investigating their proposed strategies and its implementation to rescue its struggling economy under the new global energy game. Analyses of potential risks surrounding reforms of specific PSCs and discussion of the underlying consequences is discussed in detail in this paper.
This paper emphasizes on the necessity, the impact and the probable success in implementing energy pricing reforms in Petroleum Sensitive Countries should a similar situation arise in the future. This novel study which is coupled with extensive investigation and qualitative risk/opportunity assessment summary may act as a benchmark for future studies.
Geochemical Formulary and Analysis of Hydraulic Fracturing Water Quality to Determine the Optimal Fracturing Fluid Design
Authors: Garland Robert , Fry Eric 
Published: October 2018

Abstract

BACKGROUND
A problem that many exploration and production companies face is how much impaired flowback and/or production brine can safely be reused on future completions; and what chemicals should be included in the fracturing fluid design to mitigate any concerns. The main focus will pertain to slickwater fluid designs.

METHODS
The authors used geochemical modeling hardware/software in combination with cuttings and sequential flowback analyses to acquire a full understanding of the shale constituents and mineralogy that disbands in formation. One can also determine the efficacy of the scale, clay, and iron control chemistries associated with the fracturing fluid design with sequential flow back analyses. Friction flow loop and rheology data confirm the homogeneity of the fracturing chemistries chosen for the application.

RESULTS
The data obtained from the cuttings analyses and sequential flowback studies confirm a correlation between the shale geology and flowback characteristics. This information confirms proper scale control selection and loading which will allow for a scale free formation. Microbiocide efficacy studies performed throughout the project indicate the propensity for microbiological activity and the successfulness of mitigation strategies. Friction flow loop data confirms the compatibility of the fracturing fluid constituents and the efficacy of those chemistries in stressed water conditions.

CONCLUSION
Studying geochemical formulary and water quality to develop a database for both well production and water quality of the producing well is critical in understanding water reuse. This data will allow the operator to make better decisions concerning optimal fracturing fluid design for slickwater application and proper reuse of water on subsequent hydraulic fracturing.
Plugless Completions Techniques and Evaluation in the Appalachian Basin
Authors: Blake Austin , Church Chris , Yuyi Joseph , Squires Christopher 
Published: October 2018

Abstract
The modern hydraulic fracturing process in unconventional shales has relied mainly on the use of mechanical isolation techniques (frac plugs) for internal isolation in between multi-cluster perforated frac stages. Significant benefits exist if mechanical frac plugs can be successfully eliminated from well completions. Recent trends of increased lateral lengths and decreased stage spacing are driving up the number of stages per well and the desire to decrease cycle time between completion and production operations, drive the effort for finding an alternative to mechanical plugs.
This paper presents two case histories of CNX Resources’ wells that utilized various completion techniques to effectively stimulate the laterals without the use of mechanical frac plugs. These ‘plugless’ completions techniques were originally necessitated due to a problem well with a casing patch where standard plug-and-perf completions methods would have required the use of Mechanical Slim Frac Plugs (MSFP) and an undergauge bit for the drillout operation. These MSFPs are designed to pass through internal diameter restrictions and then set and seal properly inside larger diameters. However, after design evaluation, the use of MSFP for internal isolation was found to have some increased challenges associated with the removal of the plug and increased time spent during drillout operations due to the undergauge bit requirement.
Three different plugless completions techniques were selected and then evaluated as a replacement for mechanical frac plugs. Two plugless techniques included the use of a particulate diversion material known as polylactic acid (PLA). The other plugless technique required no particulate diversion material. Proppant tracers and gas tracers were used to evaluate the proppant distribution, cluster efficiency, fracture behavior, and gas returns from each of these techniques. Well productivity was compared to offset wells to quantify the overall success of the plugless completions versus standard plug-and-perf completions. Potential for numerous benefits including reductions in completions costs, operational risks, and cycle times exist with the implementation of plugless completions methods. This case study will lay a framework for operators and service companies to practice and/or evaluate different techniques in completing wells without the use of mechanical frac plugs for internal isolation.
Dynamic Logs Endorsing Nuclear Magnetic Resonance Accuracy Results with Respect to Conventional Logs in High Vertical Heterogeneity Reservoirs for Mature Fields: Case Study, Ecuador
Authors: Ramirez Carabali Nelson Xavier , Fuerte Beltran Jeimmy Elizabeth , Mata Jose Gregorio , Castillo Rommel , Cuenca Dario 
Published: October 2018

Abstract
This paper compares production results and the evaluation of conventional logs versus advanced logs as nuclear magnetic resonance (NMR) in a mature field, discusses vertical reservoir heterogeneity and different flow units in apparent homogeneous reservoirs, and identifies bypass reserves oil resulting from poor sweep efficiency.
A petrophysical evaluation was performed using conventional and advanced logs. Comparing the results with dynamic production logs demonstrated that the NMR evaluation was more accurate than conventional log evaluation in identifying different flow units.
Traditional interpretations with conventional tools did not identify the water entry problems caused by different flow unit systems, which resulted in production sweep effects from nearby wells. NMR identified this problem, the reservoir quality, and the vertical heterogeneity and its effect on water entry. It was determined that a uniform sweep did not exist from the bottom to the top of the reservoir; thus, the aquifer water entry depended exclusively on reservoir quality related to flow unit characterization and capacity, as permeability and seal distributions are locally developed.
Adding to this complex scenario of identifying bypassed zones and the noncorrelation with conventional logs is carbon dioxide (CO2) hiding the presence of the true porous zones, potentially leaving remaining reserves that could be overestimated or underestimated.
Comparing dynamic logs versus static logs resulted in a credible endorsement of NMR, demonstrating its advantages and accuracy over conventional logs and a better technical application for recovering the remaining reserves and optimization of a mature field.
Novel High Performing Non-Beaded Lightweight Cements with Enhanced Mechanical Properties for Enabling Faster Drilling
Authors: Pernites Roderick , Clark Jordan , Padilla Felipe , Jamison Christopher , Jordan Andy 
Published: October 2018

AbstractThe efficiency of the well construction process is highly dependent upon completion of the cementing phase. Drilling ahead is dependent on when the cement will build sufficient strength to support the existing casing. This paper presents a novel lightweight cementing technology through application of advanced chemistry that shows high potential for faster completion of the cementing phase, decreasing the waiting time for the cement to set, thereby allowing continued drilling operations. A unique lightweight density superior performing cement was successfully developed for high early compressive strength development that does not utilize traditional methods and materials for enhancing cement strengths like glass beads, cenospheres, silica fumes, fly ash, modified and/or natural clays.
Using Supervised Machine Learning Algorithms to Predict Pressure Drop in Narrow Annulus
Authors: Singh Kriti , Miska Stefan , Ozbayoglu Evren , Alp Aydin Batur 
Published: October 2018

Abstract
Narrow annulus is frequently encountered in drilling operations as in Casing while Drilling, Liner Drilling etc. Hydraulics of narrow annulus is a relatively new topic of research in drilling. Current analytical solutions have limited applicability for complex flow regimes affected by casing motion, pipe rotation, eccentricity and cuttings. Therefore, the objective of this research is to develop data-driven statistical learning models which can be very effective in making pressure loss predictions for given operating conditions. The data for proposed supervised learning was obtained from large scale experiments conducted on a narrow annulus wellbore configuration on LPAT (Low Pressure Ambient Temperature) flow loop at TUDRP, Tulsa University Research Projects Group. Exploratory visualizations were used to determine the relationship between operational parameters and pressure drop. Resampling methods, such as cross-validation and bootstrapping, were used to split the dataset into training and test data. Shrinkage and Decomposition technique was applied to make multivariate regression more robust. Comparison was made between different algorithms to determine the best model in terms of Least Mean-Squared-Error (MSE) on test data prediction and interpretability. Multivariate exploratory plots were used for data inference. Relationships between different factors and annular pressure drop were mostly linear. As expected, pressure drop increased with increase in flow-rate, inclination angle, ROP and for non-Newtonian polymeric fluids. Principal Component Analysis (PCA) was performed to reduce the dimensionality of the data set. Approximately 98% of variance in data was explained by 5 principal components and the resulting model produced a MSE less than 1% of median pressure drop. Even though PCA regression model performed well on test data, final model was more difficult to interpret because it does not perform feature selection or even produce coefficient estimates. Therefore, Partial Least Squares (PLS) regression was used which gives better model interpretability as it is supervised by feature-outcome relationship. Shrinkage methods-Lasso and Ridge Regression were also used. These methods add an additional penalty term to Least Square Regression to get a bias-variance tradeoff. Cross-validation was used to select the penalty term that gave the lowest MSE. Both methods produced competitive MSE but performed better than PCA and PLS regression. In conclusion, Lasso-Regression performed the best with lowest error and good interpretability.
Integrating Big Data Analytics Into Development Planning Optimization
Authors: Ockree Matthew , Brown Kenneth G. , Frantz Joseph , Deasy Michael , John Ramey 
Published: October 2018

Abstract
This paper reviews several Big Data analytical initiatives in the Marcellus Shale. We describe how application of Big Data technology evolved, share challenges and benefits derived from Big Data analytical processes, and discuss lessons learned. We present an overview of Big Data methods employed, show how we integrated results with economic analyses to guide field development, and summarize the significant impact on development economics.
This paper will help operators, analysts, and investors "de-mystify" Big Data technology, and provide insights and guidance to those embarking on Big Data initiatives. We discuss an ongoing initiative that employs cognitive analytics to generate production type curves via machine learning and couples the results with integrated economic analyses to guide field development. Challenges associated with data management, such as automated data QA/QC, sparse datasets, interpolation/extrapolation, model training and evaluation are discussed. Benefits derived from integrating Big Data-generated type curves with economics analyses to guide well/field optimization are also presented.
Our past big data experiences have taught us several important lessons. First, Big Data initiatives are journeys, not destinations, so expect to constantly feel like there is more to learn and do. Nonetheless, implementation of Big Data processes along the journey can add significant value to an asset, as demonstrated in this paper. Second, it is critical to clearly define the problem to be solved; without a crystal-clear mission statement, scope creep is inevitable, because Big Data technology is capable of so much. Finally, partnering with someone that has experience solving similar problems can significantly accelerate the process and add value.
Using Machine Learning to generate forecasts allows the engineers to focus their efforts on increasing business value, rather than managing and manipulating data. In the end, we will demonstrate how a process that once took multiple man-weeks of effort was solved within a single man-day of time. Finally, we present an example of an optimization opportunity identified with the potential to yield approximately 15 Bcfe in additional cumulative production, while maximizing future drilling inventory in the Marcellus Shale. (Note – this is presented as a "theoretical" example in the body of the paper.)
Innovative Play-Scale Integration of Rate Transient Analysis Data: New Stimulation Indicator and Insights on Stimulated Rock Volume Behavior With Depletion
Authors: Perrier Sebastien , Araman Alexandre , Shrestha Ashis , Shawuti Zulibukaer 
Published: October 2018

Abstract
Rate Transient Analysis (RTA) is a classic characterization method for unconventional wells. In this paper, we propose to leverage RTA rate-pressure transforms by analyzing the data at play scale, using pattern and anomaly classification algorithms, to derive new quantitative and qualitative indicators for more than 600 wells operated by Chesapeake Energy on Utica gas shale play.
This paper will present:a workflow of automated classification and extraction of RTA characteristics, including the collection of weak signals associated to well-to-well interferences.the major large-scale observation of this study: Stimulated Rock Volume (SRV) characteristics change over time
The comprehensive review of the context of occurrence of these evolutions in SRV characteristics introduces a new field of discussion on hydraulic fracture geomechanical behavior under depletion.
In particular, these evolutions of SRV characteristics occur in a fairly structured way (in term of timing and geographic distribution), and the late RTA slopes (in transient flow regime) show a strong trend of convergence toward an apparent geomechanical stable state.
These evolutions in SRV characteristics have multiple implications for the reservoir engineer as well as for the understanding/benchmarking of the performance of fracturing techniques. A new stimulation indicator is proposed, 1_m2_clusters.
New Salt-Tolerant Friction Reducers Minimize Alteration of Rock Wettability after Hydraulic Fracturing: Case Study
Authors: Liang Xu , Ogle James , Straffin Ian , Riley Howard , Padilla Jose , Weiman Sam 
Published: October 2018

Abstract
Salt-tolerant cationic friction reducers (FRs) have been successfully used in up to 100% of high total-dissolved-solids- (TDS) produced water for hydraulic fracturing applications. However, they might not be compatible with formation rocks, such as sandstone, that are typically negatively charged under normal pH. This study introduces a new cationic FR (C-FR) formulation that switches to anionic conditions under downhole conditions, thereby having minimal effects on the rock wettability of sandstone or clay formation.
Flow loop and zeta potential tests were conducted to demonstrate the benefits of using a C-FR that tends to have minimal formation damage toward formation rocks. Flow loop tests qualify the FR as a robust polymer that is salt tolerant to high levels of iron, allowing 100% reuse of produced water on location. Zeta potential measures the rock's surface charge and determines if there is significant wettability alteration in the presence of this FR.
Flow loop results verify that the new FR is extremely salt tolerant up to 300,000 ppm of TDS that includes up to 200 ppm of iron. An initial multiple well trial program was implemented in the Marcellus during August 2015, and, on average, pumping rates were maintained at approximately 100 bbl/min, and the treating pressure was kept well below 8,000 psi. Zeta potential indicates that the FR became negatively charged after releasing the cationic compound, thereby having minimal impact on the original rock wettability. The normalized long term production data from selected wells were compared to other offset or adjacent wells fractured with a standard anionic FR; no appreciable difference was determined.
Insights into the Gas Transmission Test at Multiscale Based on Discrete-Fracture Model and History Matching
Authors: Jia Bao , Tsau Jyun-Syung , Barati Reza 
Published: October 2018

Abstract
A deep insight into tight gas transient flow behavior is important for understanding the production behavior of tight gas reservoirs. In this work, we constructed a two-dimensional model to illustrate one methodology of evaluating effective permeability of fractured flow media. Pulse-decay experiments on one fractured core to study porosity and permeability for both matrix and the fracture, under a series of pore pressure and effective stress. Based on the results, the approach proposed in this study has the advantage over the steady-state method that can capture the character of transient flow if the fracture network penetrates the core. The transient gas propagation in the matrix, fractured cored with the fracture width of 1 μm and 1 cm are in shapes of piston-like, arrow-like, and dumbbell-like, respectively. Though the fracture width is only 1 μm, it reduces the time to reach pressure equilibrium to about one-fourth and the effective permeably ratio is 3.98. Totally 59 pulse-decay experiments were performed on one fractured core. We successfully history matched all the pulse-decay experiments on a fractured core by a commercial simulator with the Global Match Error (GME) less than 0.2%, that the readers can readily adopt this approach. Based on the history matching of upstream and downstream pressure curves, the fracture permeability and porosity are 6 orders’ and 1 order's magnitude higher than the matrix. The matrix permeability is the most sensitive to the pore pressure and effective stress, and no consistent trend is observed for the fracture permeability and porosity as the pore pressure and effective stress change.
The Role of Machine Learning in Drilling Operations; A Review
Authors: Noshi Christine I. , Schubert Jerome J. 
Published: October 2018

Abstract
Drilling problems such as stick slip vibration/hole cleaning, pipe failures, loss of circulation, BHA whirl, stuck pipe incidents, excessive torque and drag, low ROP, bit wear, formation damage and borehole instability, and the drilling of highly tortuous wells have only been tackled using physics-based models. Despite the mammoth generation of real-time metadata, there is a tremendous gap between statistical based models and empirical, mathematical, and physical-based models. Data mining techniques have made prominent contributions across a broad spectrum of industries. Its value is widely appreciated in a variety of applications, but its potential has not been fully tapped in the oil and gas industry. This paper presents a review compiling several years of Data Analytics applications in the drilling operations. This review discusses the benefits, deficiencies of the present practices, challenges, and novel applications under development to overcome industry deficiencies. This study encompasses a comprehensive compilation of data mining algorithms and industry applications from a predictive analytics standpoint using supervised and unsupervised advanced analytics algorithms to identify hidden patterns and help mitigate drilling challenges.
Traditional data preparation and analysis methods are not sufficiently capable of rapid information extraction and clear visualization of big complicated data sets. Due to the petroleum industry's unfulfilled demand, Machine Learning (ML)-assisted industry workflow in the fields of drilling optimization and real time parameter analysis and mitigation is presented.
This paper summarizes data analytics case studies, workflows, and lessons learnt that would allow field personnel, engineers, and management to quickly interpret trends, detect failure patterns in operations, diagnose problems, and execute remedial actions to monitor and safeguard operations. The presence of such a comprehensive workflow can minimize tool failure, save millions in replacement costs and maintenance, NPV, lost production, minimize industry bias, and drive intelligent business decisions. This study will identify areas of improvement and opportunities to mitigate malpractices. Data exploitation via the proposed platform is based on well-established ML and data mining algorithms in computer sciences and statistical literature. This approach enables safe operations and handling of extremely large data bases, hence, facilitating tough decision-making processes.