bluuebunny/crossref_metadata_2025_split huggingface dataset:
Petroleum Engineering Curricula: Is it Better to Enhance Geographical Diversity or to Standardize International Education?
Authors: Falcone G. , Teodoriu C. , Barrufet M. 
Published: September 2013

Abstract
While it is commonly accepted that a job in petroleum engineering (PE) typically involves international traveling and assignments abroad, PE curricula around the globe still tend to reflect country-specific traditions and the needs of the local oil and gas industry.
Historically, oil and gas schools had a focus on local market needs, but more recently, several US and UK institutions have opened campuses in the Middle East, which mirror their original curricula at home. These initiatives were a response to local needs for qualified PEs to international standards.
Today, PE programs compete nationally and internationally to recruit top students and deliver top graduates. Inevitably, this makes one wonder whether the oil and gas industry would benefit from a standardized, international PE curriculum. For example, the SPE has already put significant effort into the harmonization of PE studies.
The paper sets out what the industry believes it wants from its PE graduates regarding their skills and behaviors. Then, based on the authors' own experience of selected PE curricula from USA and Europe and, by focusing on the Master of Science (MS) level, it compares the relative benefits of having a 1-year or 2-year MS program. It asks whether these programs should produce rounded PE graduates or specialized practitioners in given sub-disciplines. Finally, the paper discusses whether the industry would benefit more from a standardized, international PE curriculum or from region-specific programs, reflecting the traditional expertise and local technical priorities.
Identifying Small Leaks with Ultrasonic Leak Detection-Lessons Learned in Alaska
Authors: Julian J. Y. , Duerr A. D. , Jackson J. C. , Johns J. E. 
Published: September 2013

Abstract
Detection of very small tubing leaks (less than one gpm) is difficult using conventional logging techniques such as spinners and temperature logs. Leak identification is an even greater challenge for leaks behind tubing. Ultrasonic leak detection was introduced in 2005 to Alaska, and 260 logs have been run to date with an 88% success rate. Leak identification has been accomplished in wellheads, tubing, tubing connections, jewelry, gas lift mandrels, packers and production casing.
Development of this tool to be conveyed on memory with wireline and coiled tubing has resulted in cost savings due to rig up efficiencies. It has also led to additional opportunities for logging higher pressure wells in which it is difficult to maintain a pressure seal with electric line.
The ultrasonic logging tool incorporates data acquisition equipment and filtering algorithms which allow continuous logging, filtering out the "road noise" of the tool as it travels up and down the wellbore. This advantage makes it far superior to old-style noise logs which require time consuming stationary counts. Ultrasound energy attenuates very rapidly, but has the ability to transmit through tubulars, wellbore fluids, and cement. These two attributes allow pinpoint accuracy for leaks as small as 0.005 gallons per minute (gpm) even behind multiple strings of tubulars. The advantage of finding small leaks is that once the leak is identified, the well can often be remediated without the use of a rig at a fraction of the cost.
Application of this tool has great significance for any operator concerned with well integrity, and particularly, in areas where rig workovers are expensive, including remote, offshore, and arctic locations. This paper discusses the history and success rate of jobs performed to date in Alaska. It provides success statistics for both real-time and memory mode, and details non-rig remediation success and lessons learned in field operations.
Applying Calibration to Improve Uncertainty Assessment
Authors: Fondren Mark E. , McVay Duane A. , Gonzalez Raul A. 
Published: September 2013

Abstract
The oil and gas industry is full of uncertainty. In addition to significant subsurface uncertainty and uncertainty in oil and gas prices, there are other risks, e.g., political, that contribute to uncertainty in oil and gas projects. Capen (1976) demonstrated that industry routinely underestimates uncertainty, often significantly. The cost associated with underestimating uncertainty, or overconfidence, can be substantial. According to McVay and Dossary (2012), moderate overconfidence and optimism can result in expected portfolio disappointment of more than 30%. While McVay and Dossary assessed the cost of underestimating uncertainty, they did not fully address how to better assess uncertainty. Capen and other authors have suggested that uncertainty can be best assessed through look-backs and calibration, i.e., comparing actual results to probabilistic predictions over time. While many recognize the importance of look-backs, calibration of probabilistic estimates does not appear to be commonly practiced in the industry. Part of the reason for this is lack of systematic processes and software for calibration.
We developed a relational database application to track probabilistic estimates and assess their reliability over time. The Brier score and its components, mainly calibration, are used for assessing reliability. The system is general in the types of estimates and forecasts that it can monitor, such as production, reserves, times, costs, and quarterly earnings. Probabilistic forecasts may be assessed visually, using calibration charts, and quantitatively, using calibration and Brier scores. The calibration information can be used to modify probabilistic estimation and forecasting processes as needed to be more reliable. Calibration results from historical forecasts may be used to externally adjust future forecasts so they are better calibrated. Three experiments with historical data sets of predicted vs. actual quantities are presented to demonstrate that use of probabilistic forecast calibration results improves future forecasts. Consistent application of this approach and database application over time should improve probabilistic forecasts, resulting in improved company and industry performance.
Calculation of Erosional Velocity Due to Liquid Droplets with Application to Oil and Gas Industry Production
Authors: Arabnejad H. , Shirazi S. A. , McLaury B. S. , Shadley J. R. 
Published: September 2013

Abstract
The American Petroleum Institute Recommended Practice 14E (API RP 14E) describes a method for calculating an "erosional" velocity, a threshold velocity at which it is presumably safe to operate. The origin of this guideline appears to remain a mystery, but some authors and operators assume that the basis for API RP 14E is erosion due to liquid droplet impacts. However, there is no experimental evidence supporting this idea. In this work, a method has been developed to calculate erosion resulting from liquid impact for pipeline materials that are used in oil and gas industry applications. Material loss data has been collected for several oil field materials such as stainless and carbon steels, chromium alloys, inconel and duplex utilizing specimens that were mounted on a rotating flywheel and impacting liquid jets. The data and American Society for Testing and Materials (ASTM) G73 guideline are combined to develop a method for calculating erosion resulting from liquid droplets impacting the surface of the pipe materials under specific flow conditions. The results from this model have been compared to data provided in the literature for both liquid jets and droplets impacting specimens utilizing different materials, droplet sizes or jet diameters and velocities. Although the model was developed based on data at relatively low velocity conditions, the results agree well with data for a variety of flow speeds and conditions. Furthermore, the model for liquid impact erosion is used to predict threshold velocities for specific flow conditions for elbow geometry to avoid erosion-corrosion due to liquid impacts. Moreover, the results of this model are compared for several different flow conditions with API RP 14E. It is shown that the trend of the erosional velocity calculated by the API guideline does not correlate with the erosional velocity calculated by the present method that is based on the liquid droplet erosion model.
The model presented in this work will be improved as more data and information becomes available. An example is provided in which Computational Fluid Dynamics simulations are being used for different droplet and impinging jet diameters to improve the performance of the model.
Challenges and Opportunities of LWD Sampling: A Case Study from the Gulf of Mexico
Authors: Cartellieri A. , Pragt J. , Galvan-Sanchez F. , Meister M. 
Published: September 2013

Abstract
This paper presents the capabilities and operation of a logging-while-drilling (LWD) fluid analysis and sampling tool in a deep-water application in the Gulf of Mexico. The operation was performed during a drilling run in a high-pressure/high-temperature (HPHT) well with an expected downhole pressure of up to 22,000 psi and 300°F downhole temperature. This paper will show how a robust fluid analysis and sampling campaign was planned and executed, matching the various objectives and technical requirements with the appropriate technology. The challenges and opportunities of LWD sampling will be discussed, especially under tough environmental conditions.
The advantages of LWD sampling systems are well known, such as shorter pump-out time due to less invasion and the ability to capture reservoir fluid samples in extended reach drilling or highly deviated wells, which provides a new application range compared to current wireline systems. As the harsh drilling environment generates severe shocks and vibration, it requires precaution in the tool design and the selection of suitable components. The influence of the downhole dynamics on the reliability and durability of the system needs to be considered.
In response to these challenges, the new LWD tool incorporates an electro-mechanical driven drawdown pump that further improves the LWD fluid analysis and sampling service. This enables a nearly autonomous operation with the assurance that fluid phase integrity is being maintained. Automation allows optimal use of the available bandwidth to deliver the most complete set of fluid property data in real time for efficient decision making, including density, viscosity, sound speed and refractive index. It enables the operator to monitor the fluid identification (fluid ID) trend carefully and in real time, even from remote locations.
The sampling process is performed shortly after the hole is drilled and is therefore subjected to different levels of invasion and contamination arising from the effects of the drilling fluid and the reservoir properties. It will be discussed how this effects the clean-up and the ultimately achievable contamination level. The newly introduced compressibility value derived from the electro-mechanical pump offers a bulk measurement, where localized sensors observe scattered data. Examples from the application in the Gulf of Mexico (GOM) will be shown and discussed.
An outlook will be given how this technology evolves in future developments and how the operator and oil company can benefit from the new technologies in the drilling environment.
Closed Loop Automation of Downhole Weight on Bit Improves Sliding Performance and Reduces Conservatism in Unconventional Horizontal Well Development
Authors: Pink Tony , Koederitz William , Barrie Alex , Bert Dave , Overgaard Darrel 
Published: September 2013

Abstract
Today, during the development of unconventionals, the lack of knowledge of the downhole dynamics environment creates a culture of conservatism where excessive safety margins need to be applied to prevent damage to the rig equipment, drill bits, drill string and sensitive drilling tools. By using downhole data in real time, this risk can be reduced and drilling performance can be significantly improved.
This paper discusses the results of the latest field test program of an automated drilling system where direct closed loop control of machines performs drilling optimization tasks using high speed downhole data. The downhole data is measured by a downhole drilling dynamics sub and is then transmitted to the surface via wired drill pipe. The downhole data is visualized and analyzed by a surface application. The surface application then sends set points through a control interface to the rig's pre-existing control system.
The paper focuses on two main areas. The first is the rate of penetration improvements that occurred, while rotating, sliding, and sliding using an automated rocking application (Maidla and Haci 2004) and secondly, the positive behavioral change that occurs when the downhole environment is fully understood.
These technologies bring significant benefit to our industry especially in the development of unconventional assets where sliding becomes slow and more challenging the longer the horizontal. The results demonstrated that these technologies significantly improve sliding performance up to 100%, especially when combined with a surface top drive rocking technology. The high speed downhole drilling dynamics data allowed the driller and the customer representatives to maximize the performance of the rig without compromising safety or the reliability of the equipment.
Unconventional Completions: Which one is Right for Your Application?
Authors: Burton W. Aaron 
Published: September 2013

Abstract
In the last five years North America has changed the oil and gas markets by using horizontal drilling and multistage hydraulic fracturing to unlock the hydrocarbons in low-permeability reservoirs. This unexpected increase in natural gas production over a short period of time in the US has led to extremely low prices due to over-supplying the market. There are indications that the US will become an exporter of natural gas, rather than an importer, as originally planned. These plays require new technologies that enable reservoir characterization, horizontal drilling, multistage completions, and multistage hydraulic fracturing. All these technologies have evolved at a very rapid pace and continue to do so. This paper will focus on the completion technologies.
Three completion techniques have emerged as the most effective and efficient in these types of formations; plug-and-perf, ball-activated completions, and coiled tubing-activated completions. The plug-and-perf technique is cemented in place and uses composite bridge plugs and perforations to isolate and divert the fracture to the correct stage. Ball-activated completions use openhole packers to isolate the annulus and ball-activated fracture (frac) sleeves to divert the fracture to the intended stage. Coiled tubing-activated completions use cement to isolate the annulus, and coiled tubing-activated sleeves or perforations to divert the frac fluid.
Each completion technique has benefits and considerations. The primary purpose of this paper is to give an overview of these completion types, discuss the benefits and considerations, and how they compare in different applications from an operations point of view. The secondary purpose of this paper is to discuss how drilling, completion, and fracturing can greatly affect each other and create limitations if these processes do not collaborate.
Fluid Hammer Increases PDC Performance through Axial and Torsional Energy at the Bit
Authors: Powell Scott , Herrington David , Botton Benoit , Ivie Brad 
Published: September 2013

Abstract
Increasing drilling efficiency and performance are key factors for determining whether or not a new play is viable for drilling. Although several factors affect drilling cost, one key element in reducing cost is reducing drilling time by increasing the rate of penetration. This is accomplished by changing the way a drill bit interacts with the formation and analyzing different ways to overcome the factors that limit drilling performance.
New performance drilling tool designs are brining conventional mud motors into the next generation with performance driven technology. This technology features the latest generation of performance elastomers with a new energy distribution system which enhances the rock failing properties of the attached bit. This is achieved by applying both axial and torsional loading to the bit at the same time.
Conventional motors are limited by torsional loading which correlates to the differential pressure a power section can hold before it stalls. The interaction between the bit and the rock correlates to this stall pressure of the power section used. The new performance technology takes this torsional load and merges it with the axial load created by the weight of the drill string, which it then oscillates axially. The combination of axial and torsional oscillating movement amplifies the cutting interaction of the bit to help overcome the compressive strength of the formation being drilled.
Due to the unique design and different available configurations, this technology is compatible with both roller cone and fixed cutter bit designs. This design allows for constant contact between the bit and formation, reducing any bit bounce or stick slip which could reduce drilling efficiency. Along with increasing bit performance it also helps reduce weight stacking by reducing friction caused from interaction between the BHA and formation. This has proven to help with weight transfer to the bit and to reduce motor stalling, thereby improving directional control.
Remote Gas Detection System Using Infrared Camera Technology and Sophisticated Gas Plume Detection Computer Algorithm
Authors: Abdel-Moati H. M. , Morris J. M. , Ruan Y. , Zeng Y. 
Published: September 2013

Abstract
ExxonMobil Research Qatar and Providence Photonics, LLC, a U.S. based firm, are undertaking research to develop a Remote Gas Detection (RGD) system that integrates computer vision algorithms and infrared (IR) optical gas imaging technology to achieve autonomous remote detection of hydrocarbon plumes. The RGD system is designed to provide continuous surveillance and early warning to operations personnel in case of gas releases and to detect fugitive gas emissions.
The RGD system utilizes a custom built IR imager and integrated cooler assembly, and a computer vision algorithm that analyzes the video output from the IR imager to determine the presence of hydrocarbon plumes. Most hydrocarbons have strong absorption peaks in a narrow mid-wave IR (MWIR) region. The algorithm takes advantage of the difference in contrast between a hydrocarbon plume and the background in an IR image and the temporal changes due to plume behavior for the analysis. The algorithm compares sequentially collected IR images and uses a multi-stage confirmation process to confirm the detection. It has multiple filters that mitigate interferences like steam and other movement of objects in the scene such as humans, vehicles, and trees. Early field tests indicate that a 4 lb/hr propane leak could be autonomously detected from a distance of up to 800 feet.
The RGD camera assembly enclosure is designed to obtained explosion proof certification using the ATEX standard for deployment at classified/hazardous areas in oil and gas processing facilities. Instrument air provides cooling and is used to purge the system. Multiple deployment opportunities at process facilities are currently underway. Results from field testing at these process facilities will help researchers investigate the effect of temperate and harsh weather conditions, the effect of varying temperatures and gain a better understanding of equipment wear and tear, maintenance requirements and life expectancies. These data sets will produce an accurate assessment of the performance of the RGD system under actual working conditions and will be used to qualify the technology for widespread adoption within the industry.
Work has also been undertaken to compare the performance of the RGD system versus existing detection technologies. The most common leak detection technology is point sensors and path infrared sensors. This technology requires dispersed gas to physically contact the point sensors or move between two path detectors. Field tests are used to compare the performance of these mature technologies to the capabilities of RGD.
Interpreting Pressure and Flow Rate Data from Permanent Downhole Gauges with Convolution-Kernel-Based Data Mining Approaches
Authors: Liu Yang , Horne Roland N. 
Published: September 2013

Abstract
The paper describes a method of analyzing data from permanent downhole gauges, even in the presence of noise, gaps and outliers. The data mining approach developed allows for the revelation of the underlying data signal, and as a useful corollary also achieves deconvolution to compute the reservoir model – even with the existence of significant noise in the data.
The convolution kernel was initially invented and applied in the domain of natural language machine learning. In the original linguistic study, the convolution kernel detected the relationship between words by decomposing words into parts, and evaluating the parts using a simple kernel function. The success of the convolution kernel method inspired us to apply it to data from permanent downhole gauges (PDG). In this study, the data mining process was conducted in two stages, namely learning and prediction processes. In the learning process, the PDG data that were decomposed into a series of pressure responses to the previous flow rate change events were used to train the convolution-kernel-based data mining algorithm until the convergence. After convergence, the reservoir model was obtained implicitly in the form of polynomials in the high-dimensional Hilbert space defined by the convolution kernel function. In the prediction process, a pressure prediction was made by the reservoir model (obtained in the learning process) to an arbitrary given flow rate history (usually a constant flow rate history for simplicity). This flow rate history and the corresponding pressure prediction revealed the reservoir model underlying the variable PDG data.
In the previous work, a series of synthetic cases and real field cases have been used to test this approach. The method recovered the reservoir model successfully in all cases. In this paper, the method was tested under problematic data situations, including the existence of significant outliers and aberrant segments, incomplete production history, and unknown initial pressure. The results suggested that: 1) the method tolerated a moderate level of outliers and aberrant segments without any preprocessing; 2) the method could reveal the reservoir model with effective rate correction when the production history was incomplete; 3) the method could reveal the reservoir model and discover the appropriate initial pressure by using an optimization on initial pressure value when the initial pressure was unknown.