bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sand Consolidation by Enzyme Mediated Calcium Carbonate Precipitation
Authors: AlAhmari Manar , Bataweel Mohammed , AlHumam Abdulmohsen , AlMajed Abdullah 
Published: November 2020

Abstract
Sand production from poorly consolidated reservoir formations has been a persistent problem in the petroleum industry. Sand production can cause erosion and corrosion to downhole and surface equipment's and loss of production. Several technologies are used to reduce sand production effects and subsequently maintain well production and safe operations. Such techniques include completion techniques, and in-situ chemical consolidation methods. The enzyme urease induced carbonate precipitation (EICP) is a reversible and environmentally friendly technique that can be used for sand consolidation. In EICP, urease enzyme catalyses the hydrolysis of urea in an aqueous solution, which results in ammonia and carbonic acid production. In the presence of calcium ions, the carbonate ions precipitate as calcium carbonate. It has been reported that urease enzyme starts losing its activity above 65 °C and thus this technology can only be applied in reservoirs with temperatures up to 65 °C. This study addresses an improved EICP method where protein is added and the technique can be applicable at high temperature reservoirs.
Two EICP solutions were prepared, EICP control solution (solution 1) which contains urease enzyme, calcium chloride and urea and modified EICP solution (solution 2) which consists of urease enzyme, calcium chloride, urea and protein. Test specimens were made by mixing sand with EICP solution and allowed to cure at different temperatures ranging from 25°C to 130 °C. Additionally, XRD analysis was performed to identify the type of calcium carbonate polymorph. SEM imaging was carried out to visualize the morphology of the calcium carbonate precipitation in the sand specimens.
Specimens treated with the solution containing protein (solution 2) had a high consolidation strength. As the temperature increases the strength of consolidation decreases in specimens treated with solution 2 and 1. However, the strength of consolidation of specimens treated with solution 2 that contains protein was considerably greater at all temperatures (up to 130 °C), than the strength of specimens treated with solution 1. Moreover, XRD analysis revealed that 70% of the calcium carbonate polymorph in solution 2 was calcite (which is the most stable polymorph). SEM images show that in the specimens treated with solution 2 the calcium carbonate precipitates at inter-particle contacts.
The impact of these results include the use of the EICP protein technique as a downhole sand consolidation method in high temperature reservoirs. Furthermore, the addition of protein in the EICP solution can lead to a reduction in the concentration of substrate and enzyme required to achieve sand consolidation, and subsequently reduction in undesirable ammonium chloride. These advantages enhance the potential use of the EICP protein system for sand consolidation in high temperature reservoirs.
ROP Enhancement in High Mud Weight Applications Using Rotary Percussion Drilling
Authors: Li Bodong , Aljohar Abdulwahab , Zhan Guodong David , Sehsah Ossama , Otaibi Ali , Suo Zhongwei 
Published: November 2020

Abstract
This paper introduces the implementation of hydro-efflux hammer as an effective rate of penetration (ROP) enhancement tool. In the test well, the target formations are mainly composed of dolomite, limestone and carbonate with hard and abrasive characteristics. In addition, the carvings caused by the unstable shale formation in the upper section result in an increased mud weight, and associated drilling difficulties and low penetration rate. The conventional drilling techniques including mud motor have not been effective in this scenario. By implementing a 9-inch hydro-efflux hammer to drilling across the given formations, a significant ROP enhancement was observed. The deployment was planned based on quantitative analysis of formation characteristics, a study on the correlation between the tool's performance parameters and formation anti-drillability parameters, and the well design. The rotary percussion drilling parameters, bottomhole assembly (BHA) and bit selection are optimized through impact resistance and bit aggressiveness analysis. The result showed an ROP enhancement of over 47% compared with the offset average, providing an effective alternative for similar applications.
How to Meet Operational Challenges in An Extreme VUCA Environment by Adaptive Process Control
Authors: Igave Abhijit Uttam 
Published: November 2020

Abstract
The energy industry has been hit hard by current global economic interruptions: rapid drops in demand, a changing mix of preferred products, plummeting crude prices, difficulty staffing essential production sites and fragile supply lines. The profound challenges facing the Oil & Gas and Refining sector have never been more evident than during the COVID19 crisis. The chemicals and refining markets are very competitive, volatile and fast paced. To maintain a strong market position, companies need to look harder and deeper into their equipment, production and operations to ensure the production chain is optimized. Industry is finding out ways on how Adapt to significant changes in operating points for your process units under this VUCA (Volatile-Uncertainty-Complexity-Ambiguity) Environment. "There is no question that we are in a VUCA environment,".
Under current "VUCA Environment", Oil & Gas, Refining Industry across the globe are facing below challenges,
Significant changes to product demand necessitate turndowns & ramp-ups to be managed safely Workforce shifting to remote and essential-only due to pandemic risk Margin optimization more critical than ever Specific energy reduction still a key objective Need for agility with product mix changes Need for sustainability of APC applications benefits
The synergy between innovations in APC model identification, automated testing, quick and easy APC retuning and controller operating modes are creating opportunities to bring new efficiencies to the process of sustaining APC controllers under this extreme VUCA environments.
Latest Innovations in the Advanced Process Control are helping Industries to maintain the Advanced Control benefits at the maximum.
State-of-the-art Adaptive Process Control solution to enable non-disruptive testing in the background to build & adapt controller models to new operating conditions Safely manage turndowns & ramp-ups via background testing & model updates. Optimize control while testing. Quickly adjust controller tuning to align with changing market conditions to be more Cost efficient and less energy consumer as operation strategy easily. Improve operating margins across enterprise with greater visibility into APC benefits and performance via Centralized Performance Monitoring. Agility as APC dynamics are automatically adjusted via variable time constants under APC Controller. Remotely monitor performance with secure data access
Integrating Drilling Dynamics into Automated Geosteering
Authors: Pare Andrew , Ferro Ardanuy Aida , Engle Caleb , Genco Andrew , Crookston Glenna , Gee Timothee , Maus Stefan 
Published: November 2020

Abstract
Developing resources in congested fields requires precise drilling to keep the wellbore in the correct stratigraphic unit and avoid collisions with existing wellbores. Automated geosteering is an advantageous method because it eliminates subjective and lengthy manual interpretation. We present an algorithm that incorporates drilling dynamics data to estimate rock strength, correlates to nearby offset wells, and locates the drill bit in stratigraphy. This new method is faster and more objective than the traditional manual interpretation.
During well planning, gamma ray intensity, sonic, and geologic logs from nearby wells are recovered and used to calculate the Confined Compressive Strength (CCS) of the stratigraphic column using empirical and physical formulas. While drilling, the algorithm receives gamma ray intensity and drilling dynamics data (e.g. weight on bit, rate of penetration, revolutions per minute, fluid flow, and differential pressure) from the subject well and calculates the Mechanical Specific Energy (MSE) of the penetrated rock. Finally, the real time MSE and gamma from the subject well are correlated automatically with the previously generated CCS and gamma logs of the offset wells to locate the drill bit in stratigraphy.
This approach to automated geosteering was tested on a large database of subject wells and offset wells from multiple basins in North America. We find that the nearby CCS logs generated from sonic data are significantly correlated with MSE values from drilling dynamics data from the subject wellbore. CCS and MSE values can therefore be used as complementary rock strength parameters for each stratigraphic unit. Furthermore, the automated geosteering algorithm has been successful in estimating the drill bit position in the stratigraphic column during real-time drilling simulations of incoming drilling dynamics data. Incorporating rock strength estimation and matching is a complementary and valuable technique to the standard gamma log interpretation for steering a wellbore to a geologic target. The automated algorithm facilitates the simultaneous correlation, in conjunction with gamma ray intensity, against multiple offset wells.
Traditionally, geosteering is accomplished by manual comparison of LWD (Logging While Drilling) gamma ray intensity with nearby gamma logs from existing offset wells. Our approach is a significant advancement because it incorporates gamma ray data and previously unused drilling dynamics data, while automating the geosteering removes laborious and subjective processes. Mature oil fields contain considerable information on rock strength and our automated geosteering algorithm makes optimal use of this information to improve wellbore positioning.
Single and Multi-Well Synthetic Well Log Generation using Multivariate Analysis
Authors: Alimohammadi Hamzeh , Mahmoudi Saman , Chen Shengnan 
Published: November 2020

Abstract
With the rapid development in machine learning (ML) and deep learning (DL) algorithms, computations power and availability of the massive amount of data, ML and DL approaches have gained a lot of interest in oil and gas industry and brought the data science and analytics into the forefront of this industry. Using traditional neural networks (NNs) to normalize log and generate synthetic well logs is not a new idea. However, the recent advancement in ML and DL methods encourages to further research and revisit the prediction power, discuss the methodological limits and further improve the approach and prediction algorithms in single and multi-well synthetic well log generation for reservoir characterization and formation evaluation.
In this study a data-driven procedure was implemented based on deep neural networks for density generation using multivariate inputs of well log data. The density prediction was formulated as a depth series regression problem where multiple inputs including different open hole logs are used as the input of a reverse model that estimates density. Different recurrent DL structures including Long Short Term Memory, Gated Recurrent Units, and Bidirectional Recurrent Neural Networks were tested in this study to select the most time-efficient and high performance model for density log generation.
The models were fed with different number of available curves to explore a relationship and potential predictive power of several variables on the target curve (density) to eliminate unnecessary and irrelevant curves and end up with a model that uses a few curves to generate the target curve. Training datasets consist of real well log data of 25 wells logged offshore Middle East. Different metrics (RMSE, MAE, and R2) were used to compare the performance of the models and stacked LSTM of three layers showed the highest performance. Using this approach companies could cut costs by generating high quality synthetic data with a faster turnaround and without the need of relogging.
Production of Methane Rocket Propellant on Mars
Authors: Al Kaissi Talal , Al Shehhi Abdulla , Marpu Prashanth Reddy , Gee Martin 
Published: November 2020

Abstract
Space exploration has made significant advances over recent years. There are now many planned robotic exploration missions for the Moon, Mars and asteroids. Carrying enough fuel for future return journeys, particularly as necessary for human exploration missions poses a key challenge, or inefficiency of having to take all required fuel for return trip for the mission, incurring significant weight penalties and opportunity cost. The UAE has announced its Mars 2117 Vision, a 100 year plan, to build a habitable settlement on Mars, and in particular: "Mars 2117aims to build the knowledge and scientific capabilities that will enable the UAE to realise humankind's universal dream of the very first sustainable settlement on the red planet within the next 100 years".
Recent exploration of Mars has identified some key in-situ raw materials regarding the presence of water ice, and an atmosphere for which the major component is carbon dioxide, comprising approx. 96%. The UAE's current Emirates Mars Mission "Hope" aims to build on that knowledge and increase our understanding with respect to the Martian climate. Future missions to Mars will lead to the development of in-situ resources. The associated technologies share many synergies with terrestrial activities concerning oil, gas and the energy industries. Furthermore, it is considered that the technology development for off-world resources may have significant advantages for terrestrial industry. The associated innovations and philosophy are consistent with the UAE's National Objectives regarding the furthering of a "Sustainable Environment and Infrastructure".
Digital BOPE Testing – A Case Study Leading to Improved Technical Assurance While Reducing Time Requirements and Cost in Onshore Drilling Operations
Authors: Anderson Mark , Halloran Sean , Hoke Gabriel , Skinner Les 
Published: November 2020

Abstract
A digital blowout prevention equipment (BOPE) pressure testing system was deployed on a remote land drilling rig in Argentina in October 2017 to replace the older testing method using an analog circular chart recorder. This paper presents a case study of that deployment, focusing on change management, cost savings, and overall BOPE testing improvement.
Results from the deployment include a 50% reduction in BOPE test time with subsequent savings that amount to 6 times the cost of the digital test equipment, improved safety, improved efficiency in addressing problems that would result in a failed test, improved data reliability, and repeatability in subsequent BOPE pressure tests.
Supply Chain Powered by AI and Blockchain
Authors: Batra Mayur , Manchanda Naresh , Moskalev Andrei , Uttamchandani Rohini 
Published: November 2020

Abstract
It is a common knowledge that the main goal of companies is to supply goods and services to buyers at maximum price for minimum cost. For companies such as energy producers, with complex and dynamic supply chains, this often causes cost control issues. Previously, business models based on VI (Vertical Integration) or outsourcing could mitigate cost increases, but these models have limits. A new paradigm is proposed: use of distributed ledger technology in the form of a blockchain-based supply chain integration solution. By permitting participants in a supply chain to integrate information flows in a secure, quick and automated levels of efficiency that are achieved and cannot be reached by other technologies and do not require participants to change their IT platforms.
The main purpose for the creation and management of the "supply chain" is for the seller to provide the buyer the maximum value – whether of a product or service – at the lowest cost. Here is a depiction of the "links" in the general supply chain for energy production.
Designing Drilling Fluids Advisory System
Authors: Al-Yam Abdullah Saleh , Wagle Vikrant B , Al-Rubaii Mohammed Murif , Abubacker Ziaudeen 
Published: November 2020

Abstract
Suitable drilling fluid with suitable properties is a critical factor in successful drilling and completion operations. Drilling fluids consultant will need information such as formation lithology, wellbore geometry, temperature, pressure to be able to formulate fluids for different sections. Drilling fluids consultants' job is to aid drilling engineers and scientists to formulate effective drilling fluids systems for the entire well sections.
The paper describes a drilling fluid advisory system with demonstrating examples to the end user. The advisory system includes a Bayesian decision network (BDN) model that utilize inputs such as temperature and pressure and provide drilling fluids formulations based on Bayesian probability determinations.
A number of drilling fluid specialists/experts feedback were gathered to develop the drilling fluid advisory system. The drilling fluid specialists/experts feedback were used to design Bayesian Network Model that would allow the end-user to take an elementary data set to obtain optimum recommendations in the area of drilling fluids.
Corrosion Resistant Alloys Test Protocol Development and Results for an Ultra Sour Reservoir Containing Elemental Sulphur
Authors: Andres Bogdan , Mizukami Akio , Pimenta Gervasio 
Published: November 2020

Abstract
Corrosion of Oil Country Tubular Goods (OCTG) is a traditional concern in the Oil and Gas industry, as it represents a major component of well integrity management. Various corrosion mechanisms may affect the performance of materials in downhole applications, especially in corrosive environments containing large amounts of H2S, CO2, and Chlorides. In high sour environments, elemental Sulphur may also be present, in which case, it will act as a strong oxidizer, affecting the performance of the material selected.
In this paper, a test methodology was developed to selected a technoeconomical fit for purpose material for application in the development of a Ultra Sour Reservoir Containing Elemental Sulphur. This methodology consisted in evaluation of the SCC (Stress Corrosion Cracking) behaviour of Corrosion Resistant Alloys (CRA) of group 4D, as per ISO15156-3/ NACE MR0175-3, at the border between 4D and 4E environmental limits including the simultaneous presence of dissolved and elemental Sulphur in the fluid.
A testing set-up was developed to ensure the contact of elemental S with the material in order to ensure the strong oxidizing reaction at the surface of the material.
The behavior of the materials was assessed by Slow Strain rate testing (SSRT), C-Ring Sulphide stress cracking and Crevice corrosion test, conducted on UNS N06985. Grades sourced from three (3) distinct manufacturers were tested to evaluate different manufacturing systems (routes) and levels of cold work, which are known to be critical in the performace of the cold worked CRA materials.
Although, CRAs have a greater CAPEX due to the content of costly chemical elements: Chromium, Nickel, Molybdenum, etc, they may be cost effective in a life cycle cost analysis as they will prevent workovers, assure a higher HSE and well integrity level.
The Use of Novel Technology of Inflow Chemical Tracers in Continuous Production Surveillance of Horizontal Wells
Authors: Chaplygin Dmitry , Azamatov Marat , Khamadaliev Damir , Yashnev Viktor , Novikov Igor , Drobot Albina , Buyanov Anton , Ovchinnikov Kirill , Husein Nadir 
Published: November 2020

Abstract
The paper describes the use of new generation of inflow chemical tracer application at Salym Petroleum Development Upper-Salym oilfield as a part of Smart Field project. This kind of well surveying using indicators that allow the evaluation of the inflow composition for each hydraulic fracturing port in horizontal wells remotely, without any additional risky and costly downhole activities.
The new inflow chemical tracer technology is based on the use of nano-particle quantum dots, which give a level of high accuracy in quantitative analysis of fluid inflow. Markers, which are micromillimeter in size, are inserted into the polymer coating of the proppant. The technology involves the injection of marked polymer-coated proppant in the process of MHF (multi-stage hydraulic fracturing). Once the MHF is done, and the well is producing, the fluid samples are taken at surface and tested in a laboratory using machine learning software. Once the obtained data is interpreted, a flow profile of oil and water can be generated for each frac stage.
One of the main advantages of marker technologies is that they provide data over a long period of time, with a significant reduction in operating cost. It opens the door for new opportunities in terms of more accurate reservoir characterization and better hydrocarbon recovery. The key element of the technology is the use of specialized intelligent machine-learning software based on Random Forest algorithm to produce production flow profile.
The described methodology was used during the multi-stage hydraulic fracturing operation on oil wells 8105 and 8064 of Upper-Salym field. The volume of proppant injection at each stage was 20 tons, out of which 15 tons were of marked proppant containing a unique code for each stage. As soon as marked proppant has a contact with well fluid markers are emitted into fluid and sampling at the wellhead can be done any time when information required. The results of samples analysis are reports with graph showing quantitative distribution of water and oil production of each fracturing interval.
The new generation of inflow markers allows for continuous production, surveillance and quantitative analysis of oil and water phase from each fracturing stage. This enables better decision making to optimize the production and make better decisions for water conformance interventions. This surveillance method does not require complex and risky well interventions or production shutdowns, making it substantially more cost effective than the existing conventional methods.
Optimization of oil production, remote monitoring for risks minimization, reduction of operating costs - all these are the results of the introduction of Smart Fields technology systems in the Salym group of oilfields.