bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive Maintenance of Gas Turbine Air Inlet Systems for Enhanced Profitability as a Function of Environmental Conditions
Authors: Marwaha Gautam , Kohn Joshua 
Published: November 2019

Abstract
Increasing trends in the digitalization of gas turbine plants allow significant opportunity for utilizing predictive maintenance methods to optimize engine performance. Digital twins have been used extensively to detect anomalies, prevent failures and encourage preventive maintenance activities. An active area of research is how to shift from preventative maintenance based on current conditions, to predictive maintenance based on future conditions. Close mapping of historical engine performance against air quality metrics and ambient weather conditions allow significant progress to be made towards true predictive maintenance, by providing a greater understanding of the condition of the turbine air inlet and compressor section. This allows for increasingly accurate predictions of future engine degradation due to air inlet pressure drop and compressor degradation to a fidelity useful for scheduling maintenance needs. An economic optimization can then be performed balancing the costs of the two engine degradation modes and the corrective actions that can be taken, namely air inlet pressure drop against filter replacement interval, and compressor degradation against compressor soak wash interval. This paper describes our experience in monitoring turbine performance to predict and optimize maintenance needs in combined cycle power plants.
Application of Machine Learning to Estimate Sonic Data for Seismic Well Ties, Bongkot Field, Thailand
Authors: Sukkee Nisa , Ketmalee Thanapong , Jalernsuk Nattapon , Lemaire Renaud , Bandyopadhyay Parthasarathi 
Published: November 2019

Abstract
Seismic well tie is a critical process to verify the time-depth relationship of a well. This process requires density and sonic transit time data. However, sonic logs are usually not acquired due to cost saving, unfavorable well path, or other operational issues. Attempts to generate synthetic logs by Gardner equation, porosity correlation, or depth correlation did not provide the required accuracy. Therefore, the goal of our project was to generate synthetic sonic logs using machine learning technique for seismic well ties. This paper will compare the different methods tested, compare the results and lists the advantages of using Machine Learning.
This approach uses machine learning technique to create synthetic sonic logs. The machine learning model is trained to predict sonic log from other relevant logs. The model representativeness is confirmed by blind tests, which consists of two steps. The first step compares the synthetic sonic logs to the actual sonic logs. In the second step, four synthetic seismograms are generated from actual sonic, machine learning synthetic sonic, Gardner predicted sonic, and averaged constant sonic. The seismic well ties are compared between those four synthetic seismograms. Once the machine learning synthetic and actual logs show similar results, the model is deemed good and can be applied on wells that do not have sonic logs. The synthetic seismograms are then generated using synthetic sonic logs for all the wells that do not have actual sonic logs.
The use of synthetic sonic logs gives us the ability to Generate synthetic seismogram to tie wells that do not have sonic dataReduce the number sonic data acquisition, saving time and moneyReduce the risk of long logging string getting stuck in the hole that would requires fishing operations and its associated cost.
First Commercial Use of New Steerable Liner Drilling Technology Delivers Early Returns for North Slope Operator
Authors: Grymalyuk Sergiy , Regener Thorsten , Mensch Robert , Canizares Paul E , Miller Troy , Hobbs Greg , Marushack Andy , Njoku Johnson , Alvord Chip , Robinson Shon 
Published: November 2019

Abstract
This paper presents and discusses the results of the first six field deployments of a newly enhanced 7-in. steerable drilling liner system in Alaska's Greater Mooses Tooth (GMT) project. The system was operated with a managed pressure drilling service and drilled three-dimensional directional objectives while casing an 8¾-in. hole section through a highly unstable overburden section to the top of the reservoir section. The shales of the overburden section were chaotically disturbed by a prehistoric landslide that left large sections in unknown orientations from the original bedding planes. These sections have subsequently proven mechanically unstable when drilled at high angles. Exploration wells in the area determined that conventional drilling and casing methods would not allow successful completion of development wells. To succeed, the GMT project needed systems that would guarantee reservoir access and well mechanical integrity. The operator elected to deploy the newest version of the steerable drilling liner system because its design indicated a higher performance potential with more fail-safe options to manage the risks presented by this interval.
The new system uses a 4¾-in. pilot bottomhole assembly (BHA) and an expandable underreamer capable of opening the pilot hole from 6-in. to 8¾-in. for the 7-in. liner that is run in parallel with the drillpipe. The underreamer blade design was customized for the application to minimize drilling dysfunctions and optimize penetration rates. Special operating procedures were applied to deploy managed pressure drilling, surveying with a measurement while drilling (MWD) tool below a motor, and drilling with up to three cutting structures engaged at the same time. A new liner cementing concept was developed and proven to enhance reliability and provide flexibility for various contingency options.
The high-risk overburden sections were simultaneously directionally drilled and evaluated with logging while drilling (LWD) measurements while they were secured with the liner to the top of the pay section below. In the first two wells, the planned 18-day deployment was completed in nine days. The duration for the drilling part of the operation planned for 10 days was completed, on average, within 2.5 days without any tool failures or high dynamic dysfunctions while averaging a rate of penetration (ROP) of 35 to 45 ft/hr. Acceptable cementation of the liners was achieved on both wells with bond results comparable to conventional cementing in the section.
This paper summarizes and describes the results and system features in detail, and demonstrates how they can help operators reducing operational risks and saving cost.
Performance Evaluation of Novel Polymers for CO2 Foam Enhanced Oil Recovery
Authors: Majeed Talha , Kamal Muhammad Shahzad , Solling Theis , Mahboob Ahmad , Zhou Xianmin 
Published: November 2019

Abstract
The oil recovery from foam flooding mainly depends on the stability of the foam flow in porous media. At severe reservoir conditions, CO2 foam becomes unstable due to water drainage and gas diffusion through the lamella. The petroleum industry is using several foaming agents to produce and stabilize the CO2 foams. These are mainly water-soluble surfactants, CO2 soluble surfactants, nanoparticles, and water-soluble polymers. Addition of a water-soluble polymer in a conventional foam can increase foam stability, viscosity, and oil tolerance. Most of the previous studies utilized partially hydrolyzed polyacrylamide (HPAM) for CO2 foam stabilization. However, the data on CO2 foam stabilization using other polymers is limited.
In this work, CO2 foam stability was assessed using several novel polymers. The foam was generated using alpha olefin sulfonate (AOS) surfactant at a constant concentration. These polymers were mainly acrylamide-based sulfonated polymers that contain thermally stable monomers that increase salt tolerance and thermal stability. The foamability, foam stability, foam diameter and bubble count per unit area of different foaming systems were measured using a dynamic foam analyzer.
The result showed that the addition of polymers enhanced foam stability and reduced liquid drainage. Novel sulfonated polymers showed much better performance compared to the conventional HPAM polymer. Reduction in liquid drainage rate was much higher for sulfonated polymers compared to the conventional HPAM due to viscosity of the foaming solutions. For HPAM, the viscosity of the solution reduced at high temperature in presence of salts whereas sulfonated polymers maintained a high viscosity in the presence of salts that resulted in less liquid drainage and enhanced foam stability. The foam stability was also assessed using foam structure analysis.
This is the first systematic study on the application of sulfonated polymer with varying molecular weight and structure for CO2 foam stabilization. This study helps in understanding the role of polymer molecular structure, molecular weight, and degree of hydrolysis on foam stabilization for CO2 -EOR.
Casing While Drilling Step Changes Performance for Complex Deviated Wells in the Middle East
Authors: Centeno Manuel , Krikor Ara , Herrera Delimar Cristobal , Sanderson Martin , Carasco Anant , Dundin Alexander , Salaheldin Ahmed , Jokhi Ayomarz , Ibrahim Sameh , Wehaidah Talal 
Published: November 2019

Abstract
The complexity of drilling highly deviated wells in Kuwait drives the need for step changing in the well construction mindset, where severe to complete loss of circulation in Shuaiba formation significantly deteriorate the shale layers in Wara and Burgan formations leading to uncontrolled wellbore stability events.
Casing while drilling (CWD) and two-stage cementing with a light density cement slurry were introduced as a technology system to drill the highly deviated complex wells through unstable and highly fractured formations. Fit for purpose engineering processes, advanced software solutions, a tailored bit and a bottom hole assembly dynamically simulated for drilling stability and directional tendency behavior were designed.
A special light density cement slurry with high compressive strength was also designed to tackle the lost circulation issues when cementing the casing string.
The paper will describe how the technologies can work as one system to solve complicated wellbore problems and address the problematic challenges of drilling unstable shales and fractured formations in the same section of the wellbore. This strategy enabled a significant time saving compared to drilling the section conventionally, removing Non-Productive Time (NPT) resulting from additional trips, cement plugs, stuck pipe, and subsequent sidetracks.
Civil Engineering Challenges in Brownfield Projects - A Case Study
Authors: Nuthanapati Sreekanth , Adel Khalid , Al Awadhi Ibrahim 
Published: November 2019

Abstract
Expansion / Debottlenecking of Industrial or Oil & Gas plants is a common phenomenon and many a times such expansion has to be located within limited plot boundaries posing multiple challenges in locating the equipment and design & execution of supporting civil structures. In some cases, finalized supporting civil structures are not feasible to implement due to additional challenges such as additional underground utilities not identified in as-built survey that may arise during execution stage affecting project schedule. Generally, such unique design challenges are not encountered in Greenfield project development.
This paper presents the typical constraints encountered in expansion projects, key parameters required to finalize the innovative solutions and measures / methods adopted to overcome the constraints in most effective and economical way in one of the major brownfield project without affecting safe functioning of existing plant.
Vibration transmissibility to structures / equipment from new equipment or old equipment vice versa, physical constraints in supporting / routing new piping, underground utilities present in the plot are some of the major challenges faced during detail engineering. Enhancing existing supporting structures for new codal requirements (e.g. revised seismic definition) and enhanced design life to support additional loads of new project in addition to existing ones are some of the additional challenge faced during engineering and construction of the brown field projects
Key parameters to be studied / considered while arriving optimal civil engineering solutions to challenges encountered, dynamic properties of new or existing equipment, foot print and founding details of existing foundations, underground utilities present in the plot / boundaries, presence of ground water table, execution feasibility of proposed new civil structures under plant operating conditions thereby avoiding plant or unit shutdowns etc. The solution arrived may have to be revised based on additional challenges that may unfold during execution stage.
Fit for purpose supporting structure configurations, out of box structural designs, usage of unique material etc., are some of the methods adopted in arriving safe and economically sound design to overcome the constraints.
Brownfield expansion in constrained plots of existing plants is a common phenomenon in all industries. Fit-for-purpose solution needs to be arrived considering constraints applicable to that equipment / plot while maintaining Plant safety and integrity. Similar approaches may be adopted to mitigate challenges in brownfield expansion of other plants to arrive at cost-effective & safe solutions.
Applying High Rate Coiled Tubing with Fiber Optic System to Meet the Growing Challenges of Coiled Tubing Interventions in Sour Gas Producer Wells
Authors: Al-Zaid Mustafa , Bulekbay Aslan , Al-Harbi Abdulaziz , Al-Driweesh Saad 
Published: November 2019

Abstract
Dealing with tight high pressure/high temperature (HPHT) sour gas reservoirs encounters many challenges. One challenge associated with these reservoirs is the development of hard and heavy scale mixture in the production tubing, causing flow and accessibility restrictions. To restore full accessibility, a mechanical de-scaling operations using special milling and cleanout assemblies is the best current solution to this problem, due to the fact that chemical dissolving methods do not deliver the desired results. Another challenge is conventional perforation in some tight wells gives limited penetration, which does not establish the required wellbore reservoir communication. In this case, utilizing the abrasive jetting tool will offer the best solution to overcome the casing string, cement, formation damage achieve optimum penetration which will optimize the stimulation design and enhance the well productivity.
In recent years, using coiled tubing (CT) equipped with fiber optics with aforementioned coil tubing intervention operations, have become a common practice in gas wells. Using this system provides the ability to acquire on-job real time data such as pressure, temperature and gamma ray depth correlation. Furthermore, the incorporation of a new rugged fiber optics system into the intervention strategy has enabled increasing operational success rate and results in robust control on the operation parameters, minimizing the risk of gas influx, reducing coil tubing runs and improving decision making process during the operations.
This paper describes the challenges in mechanical de-scaling and slot cuttings operations, overview of different applications using CT with fiber optics system, provides a comparison between the rugged and standard fiber optics systems and lessons learned of recent implementation of the rugged CT fiber optic system.
Comparative Analysis of Intelligent Algorithms to Predict the Minimum Miscibility Pressure for Hydrocarbon Gas Flooding
Authors: Khan Mohammad Rasheed , Kalam Shams , Khan Rizwan Ahmed , Tariq Zeeshan , Abdulraheem Abdulazeez 
Published: November 2019

Abstract
Over the past two decades, enhanced oil recovery (EOR) has become one of the prominent techniques to increase the recovery of reservoir. EOR consist of four different techniques i.e. thermal, chemical, microbial and gas injection. Gas injection/flooding is one of the most robust applied technique for light oil EOR. Gas injection/flooding comprise of two processes called miscible gas flooding and immiscible gas flooding. Miscible gas flooding is the process in which both injection fluid and reservoir fluid are miscible. The minimum pressure at which both injecting, and reservoir fluids are miscible–is commonly known as Minimum Miscibility Pressure (MMP). The estimation of MMP is the challenging and crucial task in the designing of miscible gas flooding. In this study, we used experimental data along with the machine learning algorithms to find out the relation for MMP. Moreover, the comparison between three different algorithms (Support Vector Machine (SVM), Functional Network (FN) and Artificial Neural Networks (ANN)) was performed based on the results of statistical analysis.
A new empirical correlation was established to estimate MMP as a function of reservoir temperature, reservoir oil composition, and injected gas composition. Since the data set contains reservoir composition data, the developed correlation incorporates the condensing/vaporizing mechanism during the miscible gas flooding process.
The data set used to establish the new empirical correlations was based on experimental data obtained from literature. The data set was separated into two parts called development data and testing and validation data. To establish the new correlations, development data comprising of 70% of the data was used. Whereas, the rest 30% was kept solely to perform testing and validation of the developed correlations. Three different machine learning algorithms called Artificial Neural Networks (ANN), Support Vector Machine (SVM), Functional Network (FN) were used to develop the new correlation. The parameters of each algorithm were optimized to find out the best correlation. For ANN, the number of neurons, weights, and bias were optimized. Whereas for SVM, the epsilon and kernel parameters were tweaked to yield an accurate model. Likewise, for FN model a backward elimination method was found to be the best learning algorithm.
To assess the performance of the developed correlations, statistical analysis was performed. Moreover, to avoid the occurrence of local minimum, multiple realizations (total 5000) with different algorithm parameters were run. The results indicated a minimal and acceptable average absolute error. Based on error, ANN was found to give the best correlation for prediction of MMP.
Reliability Management Digitalization in Oman Gas Company, A Best Practice in Midstream
Authors: Al-Noumani Faisal 
Published: November 2019

Abstract
Digitalization in Oil & Gas industry is essential to move straight forward into industry 4.0 revaluation. All data of assets operation interconnect in one digital platform that helps to analysis data, and optimize process in order to improve economically business target and minimize risk by increasing assets reliability. Oman Gas Company (OGC) reliability management journey provides the cornerstone for developing a culture that safety & environment incidents and equipment breakdown are preventable. The OGC journey in reliability digitalization started with one digital platform that consists of all assets field condition data, and then semi-auto analysis to end up with continues improvements recommendations. The collected asset condition data from field, are the core information used for analysis, which include all occurred failures, downtimes, First Line Maintenance (FLM) checks, maintenance inspection data, process data, alarms, offline/online condition monitoring and as well linked to CMMS (SAP), which all are digitalized using connected a cyber-networking and handheld devices. Analyze & use of all these data are the key of asset performance management, that include reliability, availability, MTBF, MTTR, failure rate, failure mode & bad actors identification, ECA, RCA, RCM validation, process optimization, alarms rationalization and risk assessment. The generated recommendations and corrective actions including repair, upgrade, optimization or adjustment, are all supporting assets reliability & performance improvement. In Oil & Gas industry, the value of the asset and its performance are influencing the operational cost (OPEX) positively in short & long term.
Dynamical Analysis of Phase Inversion in Oil-Water Mixtures
Authors: Al-Jindan Jana , Ahmed Yusuf , Noui-Mehidi Mohamed Nabil 
Published: November 2019

Abstract
In the present paper, a dynamical signal analysis of oil-water dispersion is presented. The focus is on phase inversion physics and the associated dynamical features of collected signals from an acoustic receptor placed within a flow setup where phase inversion where triggered when needed. The acoustic fields associated with the mixing system showed clear differences between oil continuous and water continuous media, phase inversion could be clearly identified from the acquired sensor signals. The dynamical analysis of the experimental data showed characteristic frequency transitions as well as specific attractors. The analysis tools could be used in field application to monitor oil-water flows for flow assurance purposes.
Hydrocarbon Exploration Potential in Migration Pathways
Authors: Taher Ahmed 
Published: November 2019

Abstract
Part of the hydrocarbons generated in the mature kitchens migrate into the conventional traps while the other portions remain in the kitchens as unconventional resources. However, significant part of the generated hydrocarbons could be available in the migration pathways.
Hydrocarbons in the migration pathways are either retained in the rocks in migration routes or accumulated in subtle traps due to the presence of heterogeneities along the migration pathways.
The migration pathways traps are envisaged to be developed in response to the presence of an equilibrium state between the buoyancy forces that are trying to move the hydrocarbon through the rocks and the capillary pressures in the low permeable layers that are resisting these movements (figure 1). The only requirement to develop such traps is for the capillary pressure to be greater than the migration buoyancy force. Smaller pore throat sizes will greatly enhance the seal capacity, especially for the larger oil molecules that are expelled during early oil migration and result in longer oil columns.
The Upper Thamama migration pathways, in east and central Abu Dhabi may represent one of the most potential areas for the secondary migration pathways oil accumulations. Some of the well-known conventional fields in these areas in reality were developed in response to the presence of heterogeneities along the migration pathways. Also, the stratigraphic traps of Mishrif and Mauddud formations in west onshore Abu Dhabi are other examples of the migration pathways hydrocarbon exploration potential.
The exploration activities in the migration pathways will rely heavily on technological improvements in seismic imaging, basin modeling, horizontal drilling, frac testing and steam injection. These will result in discovering a commercial volume of hydrocarbons along the migration pathways.