bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Ceramic Proppant Alternative for Deep Conventional Gas Development in Saudi Arabia
Authors: Fraim Michael , Al-Awaji Saleh 
Published: March 2019

Abstract
The purpose of the paper is to present the results of using local sand resources in Saudi Arabia for the manufacture of resin coated proppant as a ceramic proppant alternative for deep conventional gas development. Crushed Miocene sandstone, old river sand and dune sand has been tested for a source to manufacture resin coated sand proppant. Compared to Northern White Sand in USA, each sand source has its own set of limitations such as angularity, low aspect ratio, clay, carbonate scale or iron oxide coating, and/or micro-fracture damage. Complete resin bonding to the particle surface required clean quartz surface free of sharp edges and no dust contamination. Conductivity testing of the resin coated sand at reservoir pressure and temperature reveals that over 95 wt% of the mesh sized sand particles should pass the room temperature crush test before coating.
Classification and Suppression of Blending Noise Using Convolutional Neural Networks
Authors: Baardman Rolf , Tsingas Constantine 
Published: March 2019

Abstract
Over the last few years, machine learning has become more and more a topic of interest in the seismic industry. In seismic interpretation like fault/salt dome detection (Amin et al. 2015, Guitton et al. 2017) and velocity picking (Smith 2017), there already have been successful implementations for some years now. Recently, machine learning was introduced in seismic processing algorithms like denoising, regularization and tomography (Araya-Polo et al. 2018) as well.
In this abstract a deblending algorithm is proposed that utilizes supervised machine learning algorithms. The method combines the two main functionalities of supervised learning, classification and regression to achieve maximum control on the deblending process. First, blended acquisition and conventional deblending methods are discussed, followed by an introduction to machine learning algorithms and how these machine learning methods can contribute to improve existing deblending algorithms. Finally, synthetic data examples are shown to illustrate the machine learning deblending approach.
A Coupled Viscosity Estimation and Reservoir Simulation for Ensemble Based Production Optimisation
Authors: Almaraghi Bashayer , Etienam Clement , Villegas Rossmary 
Published: March 2019

Abstract
In this paper we carry out a full field Reservoir calibration and optimisation scenario, coupling molecular interactions and ensemble based optimisation techniques. We use the friction theory model to estimate the viscosity, taking into account the molecular interactions and integrating the results in Reservoir simulation using the equation of state. Model calibration is achieved with the Ensemble Smoother with Multiple Data Assimilation (ES-MDA).
Further, we then optimise the calibrated model, focusing on Enhanced Oil recovery technique, with steam injection, utilising the Ensemble based Production Optimisation method (EnOPT). The Hydrocarbons viscosity was estimated using the friction theory, which utilises the attraction and repulsion parameters in a Van Der Waals type equation of state and the concept behind Amontons Coulomb friction laws. The molecular interactions are taken into account in understanding the fluid viscosity behaviour. The link is signified between the molecular interactions and their effect on the velocity between the hydrocarbon fluid layers that are responsible for the resistance to flow. The uncertainty in the estimated viscosity could be narrowed by using Bayesian statistic techniques to match the chosen reservoir parameters with the mean historical data using the Ensemble Smoother with Multiple Data Assimilation (ES-MDA).
The Enhanced Oil Recovery technique was chosen to be steam injection in order to reduce the oil viscosity by raising the reservoir temperature without maximising the overall cost. The Net Present Value (NPV) was maximised by using an ensemble based optimisation technique (EnOPT), where the controls of steam injection temperature and two producers bottom hole pressure were the adjusted parameters.
The viscosity of a heavy oil required additional recovery techniques to increase the driving force for the production. The heavy oil viscosity decreases with increasing temperature due to the increase in kinetic energy of the molecules that weakens the attraction force and the increases in repulsion between them. The initial mean NPV of the generated 100 realisations of the chosen adjusted parameters was found to be approximately $1,500,000.
The mean NPV of the realisations after optimisation was found to be $3,440,056. This increase in NPV was due to the increase in oil production rate, the main parameter influencing the increase in NPV was the cost and amount of oil produced, bearing in mind the water treatment and steam cost. The novelty in this study is a coupling of molecular scale simulation (friction theory) with Reservoir Simulation (by means of the Peng-Robinson Equation of state), which estimates the main physical parameters of reservoir systems and also adequately accounts for the intermolecular forces. We also calibrate the synthetic reservoir model with the ES-MDA infused with EnOPT for realistic model production optimisation.
Acoustic Properties of Carbonate: An Experimental and Modelling Study
Authors: Elhaj Murtada , Abdullatif Osman , Abdulraheem Abdulazeez , Hassan Amjed , Sultan Abdullah 
Published: March 2019

Abstract
The science of Acoustics deals with the propagation of mechanical waves in the three phases of materials, solids, liquids, and gases. In exploration and reservoir engineering, acoustic wave velocities play an essential role in reservoir description. The primary challenge in the initial evaluation and characterization of reservoirs is related to the understanding of its geology, petrophysics, and geomechanics. Therefore, an accurate estimation of acoustic wave velocities and rock porosity is essential for better reservoir description and performance as well as a better forecast of seismic properties. In this reseach, the primary objective is to analyze the texture, mineralogy, porosity and permeability data of outcrop carbonate rock samples to study the impact of confining pressure on wave velocities. Furthermore, an empirical correlation is proposed for relating porosity with acoustic properties.
Ninety outcrops samples are collected from Dam Formation in Al-Lidam area in Eastern Province, Saudi Arabia to develop a correlation. The carbonate samples varies from mudstone to grainstone facies. The samples are collected, prepared, and tested for this experimental study based on API standards. Compressional and shear wave velocities of carbonate rocks are measured under dry and fully brine-saturated conditions for 5 to 25 MPa effective confining pressures at room temperature. Moreover, porosity and permeability are measured using three different techniques, viz., AP-608 Automated Porosimeter-Permeameter, Helium Porosimeter, and thin section technique. Finally, the results are compared with those from other studies related to the same area.
A state-of-the-art review is presented on seismic properties, relationship with porosity and acoustics in addition to the current trend and the future challenges in the area. The laboratory investigations for this study reveals that Al-Lidam area has different types of facies. The results also show that both compressional and shear wave velocities increase as the confining pressure on the dry samples increase. However, the compressional wave velocities increased and the shear wave velocities decreased with confining pressure under fully saturated conditions. A new correlation is presented for carbonate rocks to predict porosity from acoustic wave velocities.
This study will help in improving the exploration efforts as well as give a better explanation for reservoir characterization, facies recognition, geophysical interpretation, and engineering calculations. This attempt will open a new research area for engineers and scientists to study the effect of variation in different properties on wave velocities.
From Pore to Process: Novel Flow Assurance Approach to Suppress Severe Production Chemistry Issues by Flow Dynamic Characterization
Authors: Alwazzan Amir , Dashtebayaz Maryam , Fiaz Mohamed 
Published: March 2019

Abstract
Dragon Oil operates the Cheleken field in the Caspian Sea offshore Turkmenistan. The production system consists of multiple wellhead and manifold platforms, a complex network of infield carbon steel and flexible flowlines to handle production from HP and LP systems and a 30" × 40 km TL to transport the produced fluids to the CPSF (Central Processing and Storage Facility) located onshore. In addition to the complexities of the flowlines network, the development has a number of unique features that pose challenges to the daily production operation activities such as: -Relatively low reservoir temperatures;-Waxy oil with high WAT (Wax Appearance Temperature) and Pour Point;-Complicated bathymetry of the 30" TL (Trunkline);-Complex reservoirs leading to uncertainty in rates;-Increasing water production;-Increasing sand ingress;-Necessity to commingle water from different sources in the flowlines;-Corrosion, erosion and emulsion occurrence;
While management of any of the Flow Assurance issues is well understood on stand-alone basis; there is no definite guidelines to manage them simultaneously through understanding their impact on each other. Obtaining flawless understanding of the nature and extent of each of the impediments issues was a key element for Dragon Oil's team to innovate this approach to minimizing the overall negative impact on production operations. The approach has been developed based on balancing the hydrophobic, hydrophilic and molecular properties of the produced fluids in correlation with the physical criteria of each of the issues to minimize the impact on the others.
This paper presents the key elements of a novel approach developed to control the impact of some issues and maintain the deliverability and integrity of the 30" TL. The approach consisted of the following activities:Conducted thorough and rigorous fluids’ analyses;Generated comprehensive operating pressure-temperature envelop during different operational and ambient conditions in the 30" TL;Constructed the occurrence envelops of Flow Assurance issues focusing on wax deposition and severe slugging;Ensured adequacy of slug catching capability at the CPSF and proper procedures to operate;Controlled gas rates to generate severe slugging in the 30" TL;Monitored the performance of the 30" TL (and eventually the system) through close observations to the changes in the key controlling parameters e.g. pressure drop, outcomes of pigging operations and efficiency of separation.
Modelling Complex Fluid Production Behaviour in a Gas Condensate Field: A Case Study
Authors: Ali Hamza , Shah Abdur Rahman , Akram Agha Hassan , Khan Waqar Ali , Siddiqui Fareed Iqbal , Waheed Abdul , Ahmed Faizan 
Published: March 2019

Abstract
A recent study addressed the modelling challenges of Alpha* gas condensate field. Alpha gas condensate field has a gas in-place of about 1 TCF, and both condensate and black oil production in addition. The field has been producing from two reservoirs S-I and D-I, for the past 26 years. Alpha field is sub-divided into two segments called the Central Area and the Northern Area which are separated by a fault as shown in Figure 2.
* Not its real name.
Application of All Reflectors Auto-Tracking Method to Characterize the Geometry and Distribution of Carbonate Shoals: An Example from the Lower Cambrian Longwangmiao Formation in the Moxi area, Sichuan Basin, Southwestern China
Authors: Chen Xiaoer , Fan Kun , Ren Chenghao , Li Le , Yan Zhenqian , Zou Guoliang , Cao Zhonglin , Zhao Yao 
Published: March 2019

Abstract
The Cambrian Longwangmiao Formation in the Sichuan Basin, southwest China, mainly comprising of dolomites, is one of the most ancient production layer in the world. Recently, Anyue gas field was discovered in the Leshan-longnvsi paleo-uplift in the central Sichuan Basin, and become the oldest gas field in the carbonate rocks in a single structural system in China. The reservoir is mainly distributed in the shoal grain dolomite, which is always controlled by the sedimentary environment. The conventional well correlation and sedimentary facies analysis might result in difficulty of carbonate shoals distribution and reservoir description in the gas field. Hence, how to characterize the geometry and distribution of carbonate shoals is critical for gas exploration and development. In our study, we completed an interpretation of 1172km2 3D seismic data in the field by means of all reflectors auto-tracking method. The method, combining density-based spatial clustering with waveform similarity clustering algorithm, can automatically track and interpret all reflectors within the 3D seismic cube. As a result, 18 local horizons, characterized by a shingled progradational configuration, were recognized within the Longwangmiao Formation. Synthetic seismograms suggest that these parallel oblique progradational sets were considered as carbonate shoals. The Longwangmiao Formation is consisted of stacked multistaged carbonate grainstones deposited on the shoals within the platform. These shoals, which grow towards northwest, are approximately distributed surrounding the Leshan-Longnvsi paleo-uplift. Stacked and widely distributed shoal grainstone reservoir is formed on the uplift. Our study suggests that the paleo-uplift mainly controls the shoal distribution in the study area, which provides important clues for gas exploration.
Gas Lift Optimization of a Mature Field of Upper Assam Basin-A Case Study
Authors: Maut Partha Protim , Changmi Titbo , Chutia Manash Jyoti , Goswami Dilip Kumar , Sharma Manas Kumar 
Published: March 2019

Abstract
Gas lift plays a major role in the oil production operations of mature depleted fields of various E&P companies worldwide. Likewise, in Oil India Limited, India about 48% of producing wells of Upper Assam Basin are on gas-lift assistance. In this project, we have started and completed a gas-lift optimization campaign in Hapjan field, one of the brown fields of Oil India Limited. This project includes complete problem troubleshooting and optimization study of all the 23 gas lifted wells of the mature field.
All gas lifted wells of the Hapjan field are intermittent lift by design and are operating with surface intermitters. As such, all available diagnostic tools developed and available for intermittent gas-lift well optimization are aggressively used during this campaign. The used tools are as mentioned below:Two-pen pressure recordings.Gas volume measurements.Acoustic surveys.Downhole pressure/temperature and long cycle surveys.Revamping of compressor station.
In the present optimization campaign, entire candidate wells of Hapjan field were included and the endeavor has resulted in crude oil production gain of 76 m3/day, which is 11.8% growth of the total production of the field. In addition, based on the results of the comprehensive study of vertical regime of the wells, 3 wells have been taken up for recompletion. Moreover, the gas volume in the injection gas network have been increased from 280000 Scmd to 340000 Scmd with the commissioning of a new compressor, and by revamping of the all other compressor units of the station. This has further supported to reallocate the required gas quantity in each individual well as per the design volume.
The technical experience and knowledge gathered from this gas lift optimization campaign certainly confirms that optimization of gas lifted wells is a vital tool to boost up production in mature depleted fields in Oil India Limited as well as in other exploration and production (E&P) operators worldwide.
A New Discovery in Complex Fault Block Oilfield Based on Dynamic Reserves Study and Fault Sealing Study: A Case Study of Bz29-4 Oilfield in Southern Bohai Bay
Authors: Gao Pengyu , Cao Long , Jiang Cong , Qin Runsen , Cui Longtao , Meng Zhonghua 
Published: March 2019

Abstract
It's difficult to fully discover all the geological reserves during exploration stage, because the fracture system of complex fault block oilfield is very complicated. As the reserve scale in single block is limited, the decline rate of the oilfield is usually very fast. As a result, finding new replacement reserves inside the oilfield is an important method to ensure stable production of complex fault block oilfields.
Base on the improvement of the Vogel method and material balance method to calculate the reservoir dynamic reserves under the degassing conditions of A14 well area. Using Allan profiling to construct lithologic docking relationship between A14 well area and adjacent fault block. Calculate SGR(Shale Gouge Ratio) for different docking areas. According to the statistics of shale content and porosity in the oilfield area, core experiment results with porosity and displacement pressure, the displacement pressure on both sides of the fault docking area can be used to predict the oil column height of adjacent block.
To ensure the initially high-speed production of A14 well area, it's necessary to reduce the times of shut-in static pressure measurement. The continuous reservoir pressure under the degassing conditions is calculated by the improvement of the Vogel method. Avoid the error of dynamic geological reserve calculation caused by too little reservoir pressure data. Result shows that the geological reserves of A14 well area is much smaller than its dynamic reserves. Study on the sealing property of faults around the A14 well area shows that the fault on the east side of the A14 well area is a non-closed fault, and the adjacent fault block is an oil-bearing fault block. Well A20 confirmed the oil-bearing properties for the fault block on the east side of the A14 well area. The result of pressure testing while drilling also shows that pressure drop in the east block of the A14 well area. All of that verify the reliability of previous research.
Aiming at the development of complex fault block oilfield, a method based on dynamic reserves research result to study the sealing property of peripheral faults to predict the height of oil columns in adjacent blocks is proposed. Achieved the purpose of finding new replacement reserves inside the oilfield. The reliability of the research is verified by the pressure testing while drilling. It provides a valuable experience for the development in similar oilfield.
Safaniya Lagoon Corporate Stewardship Biodiversity Sanctuary
Authors: Jumaan Moayad , Alsinan Ali 
Published: March 2019

Abstract
Among the many goals of environmental management in Saudi Aramco, protection of special environmental areas is recognized as high priority to both the company and the Kingdom of Saudi Arabia. In line with this objective, Safaniya Onshore Producing Department (SONPD) designated Safaniya area sea water lagoon as Corporate Stewardship Biodiversity Area. The area is estimated to be 6 km2 peninsula, which is located in the north east of the Safaniya Producing Plant, where undisturbed native flora combines with a pristine shallow sea water lagoon, and provide a safe place for land wildlife (foxes, rodents, reptiles), marine wildlife (turtles, shrimps, fish, mollusks) and birds (flamingos, seagulls, etc.). Establishment of the Safaniya Lagoon started with surveying Safaniya and Tanajib Area, in collaboration with Saudi Aramco Environmental Protection Department (EPD) to select the most suitable region for biodiversity development. An establishment procedure was followed to secure the area with fences to limit the accessibility and prevent improper usage. A signboard was installed to identify the area as a sanctuary, forbidding entrance or any type of land use. Site development included mangrove plantation, already existing trash clean-up, and observation any type of waste dumped in the area, to ensure no contamination or danger to the habitat in the lagoon. The department successfully cooperated with Saudi Aramco EPD to plant more than 9,000 mangrove seedlings at the first two years of development. SONPD in collaboration with Society of Advocates and Volunteers for the Environment (S.A.V.E) invited employees with their respected family members to participate in a biodiversity beach clean-up campaign. The campaign helped collect more than 300 kg of waste, consisting of plastic bottles, old ropes, wood, and other waste materials. SONPD, along with its partners and programs, has now established the Safaniya Lagoon ecological and biological diversity sanctuary as a permanent refuge, with in-place protection and future mangrove planting events planned, the area is expected to expand in biodiversity with native flora and fauna, and expand a natural breeding and hatchery. During the winter season, migratory birds — such as flamingos and Amur Falcons, with flyways that pass over Safaniya Lagoon — are seeking warm weather and abundant food supplies. Creation of biodiversity is just the beginning of further area development. The next phase of sanctuary enhancement will be reutilization of tertiary treated wastewater for trees, which will form a wind barrier for mangroves.
Real-Time Drilling Models Monitoring Using Artificial Intelligence
Authors: Alotaibi Bader , Aman Beshir , Nefai Mohammad 
Published: March 2019

Abstract
In recent years, the Drilling and Workover (D&WO) operations are growing significantly. The growth of active operations required and produced more data from D&WO operations. With very large number of rig activities daily transmitting more than 60,000 real-time data points every second, it became necessary to understand and utilize this Big Data in order to predict drilling troubles and discover hidden knowledge. The adaption of the industrial Revolution (IR) 4.0 contributed to the use of advanced and novel approaches such as Artificial intelligence (AI) and Machine learning (ML) models. However, those models require continues improvement as drilling data change. When using the industrial standard and adapted Wellsite Information Transfer Specification Markup Language (WITSML) based Big Data environment, the task to monitor the performance of a model at a large scale becomes challenging due to common reasons such as a large number of wells, different models being deployed and different data stored in different systems.
In this paper, a new approach is introduced using WITSML based Big Data environment. The methods employed utilize an advanced engine to monitor and evaluate active AI/ML models at a large scale. The engine utilizes anomaly detection methods to monitor abnormal behaviors of the models such as sudden high rate of alerts per day/well or a sudden drop in true event detection. The paper will also demonstrate how such technology can help in early detection of model's decay signs or sudden changes in real-time data quality.
The solution improved and automated the process of monitoring and maintaining of AI/ML models in the Drilling domain. It also made the decay detection of models possible and showed how models improve when iterative enhancements are deployed.