bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Impact of Open Hole Gravel Pack Completions to Remediate the Observed Productivity Decline in Cased Hole FracPack Completions in Deepwater Gulf of Mexico Fields
Authors: Zaki Karim , Li Yan , Terry Clinton
Published: October 2018

The objective of this work is to assess the impact on productivity decline of altering the completion type in a deepwater Miocene reservoir. Typically to date, these types of assets have utilized Cased Hole FracPack (CHFP) completions as a basis of design. Wells in the Gulf of Mexico targeting the deepwater Miocene plays have seen significant Productivity Index (PI) decline within the first few years of production.

Open Hole Gravel Pack (OHGP) and Open Hole FracPack (OHFP) completion types were selected as potential alternatives to CHFP. A coupled well, reservoir and geomechanical model was created to assess the impact of multiple potential damage components on matching the observed inflow performance from production logs. The model assesses probabilistically the weighting of each of six damage mechanisms (creep, fracture conductivity, fines migration, fracture connectivity, off-plane perforation contribution and drilling/completion fluid damage) on well performance. Based on this weighting, an assessment can then be made of their impact on the alternate completion types.

Previous studies (Knobles et al. 2017) have indicated that cased hole completions are particularly susceptible to PI decline. Specifically, when unpropped perforation tunnels collapse, they reduce the inflow area into the wellbore and create a flow restriction. In higher permeability formations, the perforations not connected to the fracture (i.e. off-plane perforations) can contribute a significant portion of the well's production. It is important to note that if the connectivity and packing of the perforations is optimized and fracture is placed to within design specifications, little PI decline is observed. However, in the real world, this is not always the case. Three wells were used in this analysis. Two wells where decline was observed and a third well where no significant decline was observed. Results from the study indicated that if the two underperforming wells had utilized an OHGP completion, the PI degradation would have been mitigated. However, the upside production seen from the third well would not be attainable had the well been completed as an OHGP on an equivalent well trajectory. The results of the study also indicated that minimizing the drilling damage would be integral to the success of the OHGP completion in comparison to optimizing the completion placement in a CHFP.

The paper addresses a significant issue of PI decline affecting deepwater wells and presents a potential remediation technique based on alternate completion types. The paper also presents a new methodology based on Design of Experiment to assess the contribution of various damage mechanism while incorporating the uncertainty around each based on available measurements.
Machine Learning Analysis of Satellite Imagery for Detection of Permian Basin Water Impoundments
Authors: Adler Joshua , Scanlon Bridget , Reedy Robert
Published: October 2018

A private company based in Houston, Texas, collects and analyzes water source, logistics, recycling and disposal data for the upstream oil and gas industry. The company recently started applying machine learning methods to satellite imagery of the Permian Basin to identify frac water impoundments and facilitate water trading between operators. Freshwater frac pond locations in Texas are not available from any public record data source, so identification of their locations and other characteristics through satellite imagery analysis may reveal new insights about energy industry operations. The company partnered with the University of Texas Bureau of Economic Geology to analyze eleven quarters of historical central Midland Basin satellite imagery, a time series beginning in January 2016, to test correlations between frac ponds and hydraulic fracturing activity. The study identified a significant positive correlation between total frac pond surface area in the satellite imagery and IHS data on aggregate water use for hydraulic fracturing in the Midland Basin area studied. This study also found a striking 76% increase in average frac pond volume over the 27-month study period, and found that the percentage of available frac pond water injected for hydraulic fracturing grew from 11% to 20% from January 2016 to July 2017. The most notable observation from this study, however, may be that the permit-based (IHS) control data appeared to lose integrity between six and ten months prior to the study date, while the satellite-derived data appeared to maintain integrity right up to the study date. As of May 2018, the IHS data shows water injected for hydraulic fracturing in the Midland Basin dropping 90% beginning in July 2017 because of absence of complete data. The satellite data, however, shows steady growth in total frac water supply throughout that period. This timeliness-of-data comparison was not the purpose of the study, but the study conclusions were limited because reliable control data could not be obtained for the time period of about ten months prior to the study date. This suggests that oilfield market research could be improved through the use of more satellite imagery analytics versus public permit and industy reported data.
Uncertainty in Petrophysical Evaluation of Thin-Bed Reservoirs in Greater Dolphin Area, Trinidad & Tobago
Authors: Gan Thomas , Kumar Ashok , Ogiste Candice
Published: October 2018

Acceptable data quality for formation evaluation forms the foundation for understanding the reservoir characterization, Petrophysical properties and pay zones identification. The data quality becomes more challenging in the thin-bed reservoirs (also known as ‘Low resistivity pay’ often abbreviated as LowReP), which poses a significant trial for field development to quantify the volumes in place and producibility.

"Greater Dolphin Area" (GDA) located within the East Coast Marine Area (ECMA) off Trinidad consists of several fields out of which this paper will be focusing on the Dolphin and Starfish fields. The reservoirs consist of a series of stacked Pleistocene sands with good porosity and permeability within a three-way-dip closure against a large growth fault. Thin-beds have been observed, verified and documented throughout this area via core acquisition, core photographs and PLT analysis. As aforementioned, due to the low resistivity pay reservoirs characteristics in Starfish and Dolphin fields, these often been overlooked or interpreted to be water-bearing, when surveyed with conventional resistivity logging tools. These thinly bedded pay section hydrocarbon volumes have significantly been underestimated between 50% – 200% deposits.

Several thin-bed methodologies have been employed for the Petrophysical modelling to support the field development planning using conventional legacy approach and Shell "Low Resistivity Pay" (LowReP) based tool response modelling and inversion methods workflow to resolve the issues associated with the presence of thin beds. This paper investigates the different methods of resolving the thin bed analysis problem and demonstrates the uncertainty of the results from each methodology on the Petrophysical properties and hydrocarbon volumes estimation.
The Industrial IoT in Oil & Gas: Use Cases
Authors: Flichy Philippe , Baudoin Claude
Published: October 2018

Since the Industrial Internet of Things (IIoT) became its own domain, in parallel with consumer-oriented IoT, various industries have been successfully deploying such systems – initially as pilot projects, and more recently at scale. Meanwhile, the O&G industry, hurt by the price of oil, postponed investments in new technologies. Nevertheless, there are now multiple successful case studies of IIoT in O&G. This paper contains a high-level review of several such IIoT projects in O&G and aims to help the reader gauge the results achieved in this area. By examining these cases and looking at the similarities and differences with applications in other industrial sectors (transportation, water management, utilities…), the O&G industry can derive guidance in its adoption of IIoT, in particular by identifying the "lowest-hanging fruit" to improve operations and reduce human and equipment costs. While there is still confusion in terms of standards, choice of technologies, and myriad actors of all sizes, this is neither new in our industry nor unexpected in an emerging field; these challenges should therefore not prevent others from moving forward.
The Benefits of Reciprocal Mentoring in the Oil and Gas Industry
Authors: Dalrymple Lori R. , Dalrymple Eldon D.
Published: October 2018

Objective/Scope

As the Oil and Gas industry looks for ways to better manage its increasingly age diverse workforce, reciprocal mentoring (RM) has become a necessity. Industry veterans are nearing retirement. Young entrants to the workforce are knowledgeable in technology, but lack industry experience. These two circumstances, along with other factors, helped create the perfect storm – the Great Crew Change.

RM can pave the way for a new standard of open dialogue in business, stretching far beyond technology. Ideally, learning and information sharing would cross all lines of seniority and responsibility.

Methods, Procedures, Process

Everyone knows that mentoring can be useful to a young employee. However, there is a lot that junior employees (millennials) can offer as mentors themselves. Senior employees were trained when technology transfer was slower and less sophisticated. They learned to give presentations without the aid of PowerPoint and other media available today. Often, they relied on a flipchart for a presentation, so they have well developed soft skills and interpersonal skills. Millennials recently graduated, have more experience in technology transfer, and recent applications and technology developed, and are more inclined to communicate through email, text, and social media. RM acts as a powerful tool to help both junior and senior employees strengthen specific skills.

Results, Observations, Conclusions

Reciprocal mentoring can create dynamic teams utilizing the overall strengths of both millennials and senior employees. These two-way conversations become avenues where employees can discuss insights from both perspectives and gain valuable knowledge from one another in an environment of trust. With the increasing number of Millennials joining the workforce in the oil and gas industry, management must incorporate new ways of mentoring them. The increase in the age gap between senior employees and millennials creates a challenge to keep the workforce engaged.

Novel/Additive Information

Differences in perspective, attitude towards work and different motivation can result in friction and an unwillingness to collaborate. This is the role of reverse mentoring which is detailed in this paper. With the "Big Crew Change" we are experiencing a shortage of younger more experienced technical professionals. Reciprocal mentoring is a way to bridge that gap.
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

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

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

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

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

The 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

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

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

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

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

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

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.
Spatial Statistical Investigation of Surface Expressions in the Midway Sunset Oil Field
Authors: Pollack Ahinoam
Published: October 2018

In the Midway Sunset Oil Field in Central California, operators inject steam into the shallow diatomite formation to enhance heavy oil recovery through imbibition, wettability alteration, and viscosity reduction, among other mechanisms. The injected steam, however, does not always remain in the reservoir or return through the wells. In two zones in the study area, the steam comes out at the surface, creating sinkholes, seeps, and steam outlets (see Figure 1b and 1c). These phenomena, called "surface expressions," pose safety and environmental hazards.

This study examines attributes of the zones with surface expressions that may contribute to their occurrence. It is hypothesized that the surface expressions are caused by leakage of steam through old improperly abandoned wells, high injection pressure, structurally controlled flow patterns, high injection volumes, or flow along naturally occurring faults, among other possible factors. Spatial statistical analysis using logistic regression and classification trees is used to explore the relationship between the surface expressions and spatial attributes. The results point to a significant spatial correlation between the surface expressions and two predictors: concentration of plugged wells and geologic seal thickness. These predictors emphasize the importance of both properly abandoning retired wells and having sufficient seal between the producing zone and the surface.
A New Computational Model to Predict Breakdown Pressures in Cased and Perforated Wells in Unconventional Reservoirs
Authors: Kurdi Mohammed
Published: October 2018

Unconventional shale reservoirs are characterised by their extreme low permeabilities and their high in-situ stresses. Multi-stage hydraulic fracturing therefore plays a key role in developing such reservoirs. However, depending on the in-situ stress magnitude and/or regime, breakdown pressures can be too extreme to achieve, given the available surface horsepower and downhole completion capabilities. This paper presents a newly developed model to predict the breakdown pressures in cased and perforated wells.

As the in-situ stresses are perturbed near the wellbore wall due to the drilled wellbore cavity, the local stresses near the wellbore wall need to be deduced. Using MATLAB software program, a transformation from the in-situ stresses to the wellbore local stresses is performed. As perforation notches also perturb the in-situ stresses, another transformation to the local stresses around the perforation notches is required. Increasing breakdown pressure causes the stresses surrounding the perforation notches to exceed the rock tensile strength. The value at which the tensile strength is exceeded dictates the required breakdown pressure.

As these transformation calculations depend on the wellbore inclination/azimuth angles, in-situ stress magnitude/regime and perforation phasing angle, a number of recommendations are presented. The results from the model recommend deep perforation penetration depths to expose the perforation tunnels to far field in-situ stresses. This eliminates the effects of local stresses and decreases the breakdown pressures. For normal faulting stress regimes, the results recommend steering the drilling bit as close as possible to Sh azimuth as any deviation results in an increase of breakdown pressure magnitude. It is also recommended to use oriented perforations rather than a typical phased perforation technique to minimize the formation breakdown pressures. The recommended oriented perforation angles depend on the in-situ stress magnitudes/regime and the wellbore trajectory.

The model aims to advance the current understanding of fracture initiation in highly deviated wells in shale reservoirs. It can also assist engineers to better select sweet spots for well and cluster placement to avoid excessive breakdown pressures and/or potential early proppant screenout.
Telemetry Data of Oilfield Facilities Analysis for the Purpose of Monitoring and Decision-Making Support at its Operation
Authors: Nafikov Tagir
Published: October 2018

In the article methods of the oilfield objects telemetry data analysis are considered for the purpose of malfunctions detection of these objects, determination of its off-nominal operating reasons and for support of management decisions making at its operation.

Telemetry production data of two objects was used: oil extraction using sucker rod pump units (SRPU) and super-high viscosity oil (HVO) production by the method of steam assisted gravity drainage.

As a result of incoming data from the SRPU monitoring system processing, an algorithm for automatic pump failures detection was developed and a method for these failures occurrence preventing was implemented.

To solve the tasks of monitoring and building of HVO wells models, a system was developed that allows to determine and visualize deviations of parameters current values from statistical models, to view models, and also to train these models on a range of selected data.
Role of Redox Processes in the Pedogenesis of Hypersaline Tidal Flat Soils on the Brazilian Coast
Authors: Sartor Lucas Resmini , Graham Robert C. , Ying Samantha C. , Otero Xosé Luis , Montes Célia Regina , Ferreira Tiago Osório
Published: October 2018

Core Ideas

Iron and Mn movement followed by oxidation impose strong control on soil transformations.

Sulfidization is not an active process in hypersaline tidal flat (HTF) soils.

Coprecipitation of Mn and ferrihydrite controls the geochemistry of Mn in HTF soil.

Hypersaline tidal flats (HTFs) represent transitional ecosystems where the ocean, land, and freshwater meet. These places are globally widespread and their soils are an important environmental component controlling chemical reactions in wetland ecosystems. Here, we present a pedogenic study of two HTFs on the Brazilian coast (northeast and southeast) based on the solid‐phase geochemistry of Fe and Mn and morphological studies. Broken and irregular topographies and strong expression of redoximorphic concentrations (e.g., mottles, nodules, and pore linings) are present throughout the soil profiles. Although lepidocrocite is the most abundant Fe fraction in these soils (more than 50% of all extractions), deeper horizons show pyrite as the main Fe fraction caused by the presence of buried mangrove soils. The more oxidizing conditions in these deeper horizons indicate that pyrite is not stable and is undergoing degradation. Iron released in this process is moving upward and precipitating as Fe oxides in more oxidized portions of the soil profile. Coprecipitation of Mn and ferrihydrite seems to be an important process controlling the geochemistry of Mn in HTFs. Our data indicate that deeper horizons have been transforming, driven mainly by water table oscillation and, consequently, redox processes. This process allows translocation of Mn2+ and Fe2+ throughout the soil profile, followed by oxidation and precipitation of Mn3+/4+ and Fe3+ oxides in preferential sites.
Molecular Topology and Other Promiscuity Determinants as Predictors of Therapeutic Class - A Theoretical Framework to Guide Drug Repositioning?
Authors: Morales Juan F. , Alberca Lucas N. , Chuguransky Sara , Di Ianni Mauricio E. , Talevi Alan , Ruiz Maria E.
Published: October 2018

Much interest has been paid in the last decade on molecular predictors of promiscuity, including
molecular weight, log P, molecular complexity, acidity constant and molecular topology, with correlations
between promiscuity and those descriptors seemingly being context-dependent. It has been observed
that certain therapeutic categories (e.g. mood disorders therapies) display a tendency to include
multi-target agents (i.e. selective non-selectivity). Numerous QSAR models based on topological descriptors
suggest that the topology of a given drug could be used to infer its therapeutic applications.
Here, we have used descriptive statistics to explore the distribution of molecular topology descriptors
and other promiscuity predictors across different therapeutic categories. Working with the publicly
available ChEMBL database and 14 molecular descriptors, both hierarchical and non-hierchical clustering
methods were applied to the descriptors mean values of the therapeutic categories after the refinement
of the database (770 drugs grouped into 34 therapeutic categories). On the other hand, another publicly
available database (repoDB) was used to retrieve cases of clinically-approved drug repositioning
examples that could be classified into the therapeutic categories considered by the aforementioned clusters
(111 cases), and the correspondence between the two studies was evaluated. Interestingly, a 3-
cluster hierarchical clustering scheme based on only 14 molecular descriptors linked to promiscuity
seem to explain up to 82.9% of approved cases of drug repurposing retrieved of repoDB. Therapeutic
categories seem to display distinctive molecular patterns, which could be used as a basis for drug screening
and drug design campaigns, and to unveil drug repurposing opportunities between particular therapeutic
categories.
Combined Virtual Screening, DFT Calculations and Molecular Dynamics Simulations to Discovery of Potent MMP-9 Inhibitors
Authors: Bahrami Hamed , Salehabadi Hafezeh , Nazari Zahra , Amanlou Massoud
Published: October 2018

Background:

Matrix metalloproteinase-9 (MMP-9) plays a crucial role in the development
and progression of cancer. Therefore, identifying its inhibitors has enjoyed numerous
attentions. In this report, a hybrid approach, including pharmacophore-based virtual screening,
docking studies, and density functional theory (DFT) binding energy calculations followed by
molecular dynamics simulations, was used to identify potential MMP-9 inhibitors.

Methods:

Pharmacophore modeling based on ARP101, as a known MMP-9 inhibitor, was performed
and followed by virtual screening of ZINC database and docking studies to introduce a set
of new ligands as candidates for potent inhibitors of MMP-9. The binding energies of MMP-9
and the selected ligands as well as ARP101, were estimated via the DFT energy calculations.
Subsequently, molecular dynamics simulations were applied to evaluate and compare the behavior
of ARP101 and the selected ligand in a dynamic environment.

Results:

(S,Z)-6-(((2,3-dihydro-1H-benzo[d]imidazol-2-yl)thio)methylene)-2-((4,6,7- trimethylquinazolin-
2-yl)amino)-1,4,5,6-tetrahydropyrimidin-4-ol, ZINC63611396, with the largest
DFT binding energy, was selected as a proper potent MMP-9 inhibitor. Molecular dynamics simulations
indicated that the new ligand was stable in the active site.

Conclusion:

The results of this study revealed that compared to the binding energies achieved
from the docking studies, the binding energies obtained from the DFT calculations were more
consistent with the intermolecular interactions. Also, the interaction between the Zinc ion and
ligand, in particular the Zn2+-ligand distance, played a profound role in the quantity of DFT
binding energies.
Betaine Aldehyde Dehydrogenase (BADH) gene and free amino acid analysis in Rhizophora mucronata Lam. from Thalassery region of Kerala, India.
Authors: Sreeshan Anusha , S.P. Meera , Augustine Anu
Published: October 2018

Mangroves are salt tolerant plants inhabiting saline environment. Multiple factors contribute to their salt tolerance and we need multifaceted approach to reveal the mechanisms of salt tolerance in the plant. In the present study, leaves of the mangrove, Rhizophora mucronata grown in the presence and absence of salt were used, free amino acids and the expression of selected genes were analyzed. Chromatographic technique showed the accumulation of free amino acids like proline, glycine, aspartic acid, valine, leucine and glutamic acid in the presence of salt. RNA was isolated from the leaf sample and cDNA was synthesized. Gene specific primers were designed and standardized. Among the genes studied (P5CS, BADH, NHX1), Betaine Aldehyde dehydrogenase (BADH) gene was found to be expressed.
Checklist of Akshara vidyalaya campus flora, Venkatachalam, Nellore, Andhra Pradesh, India.
Authors: K. Manipal , M.V. Kumuda , K. Madhava Chetty
Published: October 2018

The present study was aimed at determining the plant species richness of the Akshara Vidyalaya (AV) campus, Nellore District. For this, the species richness data was obtained by intensive surveys in the campus from 2015–2017. We recorded 247 species in 194 genera belonging to 69 families composed of 52 trees, 55 shrubs and 140 herbs, two species are parasites. Poaceae (20 genera 24 species), Fabaceae (15 genera 21 species) are the two species richness families and an inventory checklist of all the species recorded is provided. This study reveals that AV campus is diverse and rich in ornamental/alien flora.