bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Machine Learning Algorithms and Integrated Production Modelling to Improve Accuracy of Liquid Production Rate Measurements Using Multiphase Flow Meters
Authors: Nazarenko Maksim Yuryevich , Zolotukhin Anatoly Borisovich
Published: December 2021

Objectives/Scope: During the period of two years the difference between sum of daily oil flow rate measurements of each oil production well using multiphase flow meter (MPFM) and cumulative daily oil production rate measured by custody transfer meter increased overall by 5%. For some wells inaccuracy of MPFM liquid rate measurement could reach 30-50%. The main goal of this research was to improve the accuracy of multiphase flow meter production rate measurements.

Methods, Procedures, Process: More than 80 oil production wells were involved in the research, more than 100 flow rate tests were carried out. Machine learning methods such as supervised learning algorithms (linear and nonlinear regressions, method of gradient descent, finite differences algorithm, etc.) have been applied coupled with Integrated production modelling tools such as PROSPER and OpenServer in order to develop a function representing correlation between MPFM parameters and flow rate error.

Results, Observations, Conclusions: The difference between cumulative daily oil production rate measured by custody transfer meter and multiphase flow meters decreased to 0.5%. The solution has been officially applied at the oil field and saved USD 500K to the Company. The reliability of the function was then proved by the vendor of MPFMs.

Novel/Additive Information: For the first time machine learning algorithms coupled with Integrated Production modelling tools have been used to improve the accuracy of multiphase flow meter production rate measurements.
Tanks Assurance and Endorsement Extension Strategy
Authors: Khattab Sahar Abdul-Karim , Alsheebani Marwa Sami
Published: December 2021

The objective of this paper is to study various methods that can be implemented on existing or new tanks to achieve an extended endorsement period (e.g. 20 years plus) for Crude Oil Floating Roof Storage Tanks. This extended period is necessary in order to overcome anticipated future challenges in tank availability due to (i) increased production and loading, (ii) stretched major overhaul (MOH) duration due to unforeseen delays in MOH works, (iii) corrosion in bottom plates, etc. An extensive research based on international API Standard 653 "Tank Inspection, Repair, Alteration, and Reconstruction" was conducted to achieve this extended period. Initially, some COS tanks aspects were assessed based on API SPEC 653 (2014, Addendum 2, May 2020) to achieve this new Tanks Endorsement Vision, such as: (a) studying the currently applied Corrosion Protection Barriers to the COS tanks and their effectiveness to the endorsement period, (b) the adequacy of commonly applied Corrosion Protection Barriers with respect to the endorsement period, and (c) exploring possible enhancements on COS Tanks Corrosion Protection Barriers, and Monitoring systems to extend tanks endorsement period. Based on API SPEC 653 (2014, Addendum 2, May 2020), currently applied tank safeguards were found inadequate to achieve the 20 years plus tank endorsement period requirement. In order to extend tanks endorsement period, additional safeguards shall be implemented, with special attention to tank bottom plates (soil side), since corrosion problems are mostly exhibited in tank bottom plates from the soil/oil side. Multiple solutions for corrosion safeguards were explored and recommended as part of this study such as the installation of a CP system under COS tanks, as well as installation of a corrosion monitoring system, and performing routine in-service inspections for COS tanks (internal and external) as per API SPEC 653 (2014, Addendum 2, May 2020), etc. Overall, this paper provides an insight on the calculation method of tanks endorsement period, and possible tank corrosion safeguards and controls that can be implemented to extend the COS tanks endorsement period to at least 20 years. Results and recommendations studied in this paper will benefit the Oil and Gas Industry and help in overcoming future challenges.
Using Active and Passive Near-Field Hydrophones to Image the Near-Surface in Ultra-Shallow Waters Offshore Abu Dhabi
Authors: Khakimov Oleg , Gholami Yaser , Tertrais Bertrand , Cambois Guillaume , Mahgoub Mohamed
Published: December 2021

Seismic surveys are generally designed to image deep reservoirs, which leaves the near-surface woefully under-sampled. This is particularly a challenge offshore Abu Dhabi, where a complex near-surface – with karstic collapses and meandering channels – contaminates the seismic image with strong footprints. To mitigate these effects, we use near-field hydrophone data, primarily designed to QC the airgun source, for near-surface imaging.

Near-field hydrophones (NFH) are positioned about a meter above each airgun and are designed to record the source near-field pressure. They immediately capture dysfunctional or out-of-spec guns, which alerts the recording crew. Yet, in a shallow water environment, they unintentionally record seismic reflections from the near-surface, which we will use for seismic imaging.

Streamer vessels usually use two source arrays, 50 meters apart, which shoot in a flip-flop mode. The active NFH refer to the recordings directly above the shooting guns, while the passive NFH refer to the recordings from the array that is not shooting. Because the passive NFH are less contaminated by the source near-field, they are typically the preferred choice for near-surface imaging.

Waters are too shallow in offshore Abu Dhabi to use streamer vessels. Instead, seismic surveys involve ocean-bottom cables (OBC) or nodes (OBN) and smaller airgun arrays. The shooting vessels can be single-source or dual-source. While a single source vessel has only active NFH, a dual source vessel has both active and passive NFH. However, even if a dual-source vessel is used, the 50 m distance between the shooting source array and the passive NFH is too large to capture the water-bottom reflection for water-depths shallower than 25 m. For these reasons, we propose to combine both measurements, using active NFH for the very shallow section and passive NFH for the deeper section.

We have applied this technique to a recent node survey acquired offshore Abu Dhabi. By combining the active and passive NFH, a very high-resolution shallow image was obtained, which allows the interpretation of geological layers just below the water bottom. Comparisons with high resolution 2D site survey images show good agreement. Given the NFH do not require any additional acquisition and are delivered as a byproduct of standard seismic surveys, we have demonstrated that proper use of NFH can provide high quality images for pre-site survey interpretation, which reduces the need for additional – and expensive – geotechnical surveys.

This is the first published use of combined active and passive NFH in Abu Dhabi shallow waters for the purpose of imaging. The resolution of the shallow formation images allows detailed interpretation not achievable using conventional seismic data. In the long term, this technique may reduce the need for additional site survey acquisitions.
Collaborative Working Environment CWE Strategy: An Enterprise Approach to Operational Excellence
Authors: Ibrahim ElFadl Z. , Al Hendi Mariam A. , Al-Qamzi Abdulla , Ballaith Nasser A. , Al Naqbi Maha A. , Al Azawi Bahir , Al Hammadi Omar I. , Traboulay Ian , Muhamed Salim Muzahidin , Dewan Rashi
Published: December 2021

Collaborative Working Environments (CWE) are a business solution that improve the quality and speed of decision making by enriching the collaboration between teams and individuals, which results in tangible business benefits. The advantages of working in a collaborative environment are well understood in the organization and the concept is widely embraced throughout the petroleum industry.

CWEs provide seamless communication between disciplines and between teams in different locations. Traditionally, they have been used to connect staff in remote locations to teams in the headquarters, allowing real time monitoring of the health of the field, and fast decision making on operational issues and short to medium term optimization opportunities. The main goal is to be quickly alerted to events and make smarter, faster decisions using key capabilities available to the company with access to all relevant knowledge, data and analytical tools required to reach a decision. But this drive to make smarter, faster decisions is applicable to all levels of a company. In fact, it becomes increasingly important as more complex decisions are required at higher levels, which can be influenced by interpreted data, personal opinions and perceptions.

In line with strategic objective of digital transformation, a national oil company (NOC) has extensive plans to develop asset specific CWEs and enterprise level CWEs. These will be centralized collaboration facilities to provide more rigorous, effective, and consistent surveillance & optimization to help reduce deferment costs and inefficiencies and accelerate decision-making with a measurable business value to enhance HSE, Reservoir, Drilling, Well and Production system performance through emerging digital innovation. All these centers shall be equipped to receive real time and episodic data and perform exception-based surveillance through trending, analysis, and condition diagnosis. All these CWE Centers shall enable decision making with efficient multi-disciplinary collaboration to address business challenges and increase the efficiency of day-to-day operations. They will have clear roles and responsibilities serving as an integral element of the value realization across the assets.

The paper will describe the enterprise CWE strategy, key technical considerations, methodology and standards that have been set up to achieve the ultimate objective of the organization to maximize oil field recovery, eliminating non-productive time, enhancing HSE aspects and increasing profitability through the deployment of these various centers.
Successful Deployment of Metal Expandable Technology with Inner String Stage Cementing System Overcomes Well Construction Challenges in Bab Field, UAE
Authors: Mwansa Peter Levison , Varma Esha Narendra , Aguilar Victor Jose , Amorocho Alexander , McPherson Daniel , Wood Kevin , Khodr Omar
Published: December 2021

Inability to effectively isolate depleted aquifer formations due to severe losses during cementation leads to accelerated corrosion of the production casing. Per current practice, a top job is performed from surface to fill the annulus with cement, but with limited success in a severe losses’ scenario. The objective is to improve zonal isolation by applying V0 rated multiple stage cementation technology with inner string thus enhancing well integrity during the life cycle of the well.

A metal expandable annular sealing system was selected as a reliable isolation mechanism for effective cementation behind aquifers due to its ability to provide high expansion in potentially washed-out wellbores and the feature of long multi-element sealing systems with built in redundancy. The inner string operated stage cementing system provides a reliable solution to selectively and accurately place cement above the metal expandable packer whilst maintaining V0 casing integrity once closed. Additionally, the unique combination of technologies provides a cost-effective life of well solution compared to current stage cementing methodologies.

Following successful execution of three trial jobs, the multi-stage cement using V0 rated tools and an inner string was compared to similar jobs done per current cementing practices. Analysis involved reviewing the cement bond column coverage and quality (CBL) with offset wells.

Cement bond log results showed that this technique enhanced the cement column quality behind the 9 5/8" casing across the aquifer zones with moderate to good cement for the most part. Contaminated cement was observed just below the previous casing shoe and this could be addressed by adding another stage tool just above the previous casing shoe. Overall results show improved cement column quality for this section when compared to conventional jobs with similar conditions and is recommended for future use in severe to total losses scenario. In a situation where losses are seen at the previous casing shoe, a three-stage job is recommended.

Other benefits include:

Security and confidence in gas tight sealing capability and mechanical integrity Precise and conclusive operation for open, close and lock with no risk of accidental lock Ability to squeeze cement below the metal expandable packer No reduction in pressure rating regardless of OH ID and full bore ID of casing No post operation drill out required of the stage tools

V0 stage cementing tools with inner string and metal expandable annular sealing system are not available on Oil & Gas market as a single tool. Therefore, this combined technology application of solutions from different technology providers to access a dedicated solution is totally novel and creates an opportunity for future applications across the industry.
Asset Integrity Management - Implementation Plan During Front End Loading Phases
Authors: Ferrario Giorgio , Grimaldi Salvatore
Published: December 2021

Capitalization of lessons learned on Asset Integrity Management during Front End Loading phases of a green field Project Development, by defining plan for implementation of a diagnostic digital tool for reducing downtime and introduce predictive maintenance during Operation.

Eni developed a platform of Digital applications for enhanced Operations management by implementing an Integrated Asset Management (IAM) system. Advanced Analytics tool is part of it and is designed for monitoring, foreseeing and preventing production upsets and anomalies; the tool is set up by verification of areas of interest and criticalities, with identification of main equipment data sets and by the implementation and validation of predictive models. Starting from historical data, data scientists supported by experts develop algorithms capable of finding interdependencies between a set of input variables and an output variable (phenomenon to be predicted/monitored), thus detecting anomalies and criticalities.

Main areas of benefit are envisaged on Production continuity, capable of predicting problems on static and rotating equipment and giving information on the most impacting variables on the incipient problems. The tool will support technicians to help them preventing failures and out-of-specs events which may cause loss of production or asset integrity issues, with the activation of predictive maintenance and the aim to strive a continuous monitoring and improvement of plant operational performances. An Energy Efficiency predictive model will also be set up, capable of forecasting the future energy performances of the asset through the prediction of the Stationary Combustion of Carbon Dioxide (CO2) emission index (t CO2/kbbl) and providing the list of the main influencing equipment and variables. The plan for implementation of the tool from the Early phases of development help the organization on prioritizing the implementation of Digital tools as part of the execution and realization of the Asset to be delivered to the Operational personnel, by easing the transition and avoiding subsequent retrofitting carrying brownfield works and additional costs.

The implementation of Advanced Analytics tool has been embedded in a new green field initiative of a Development Project since Front End Loading phases, thus fostering digital implementation and minimizing deployment costs by including those as part of the Investment Proposal presented to Joint Venture Partners and Authorities.
Case Study of Identifying and Minimizing Formation Damage in Tight Reservoirs Caused by Drilling Fluids in Abu Dhabi Onshore Operation Using Compatibility Coreflood Studies
Authors: Saragi Raymond , Husien Mohammad , Abdullah Dalia Salim , McLaughlin Ryan , Patey Ian , Green Justin , Wright Leigh
Published: December 2021

A study was carried out to examine formation damage mechanisms caused by drilling fluids in tight reservoirs in several onshore oil fields in Abu Dhabi. Three phases of compatibility corefloods were carried out to identify potential to improve hydrocarbon recovery and examine reformulated/alternate drilling muds and treatment fluids. Interpretation was aided by novel Nano-CT quantifications and visualisations. The first phase examined the current drilling muds and showed inconsistent filtrate loss control alongside high levels of permeability alteration. These alterations were caused by retention of drilling mud constituents in the near-wellbore and incomplete clean-up of drilling mud-cakes. Based upon these results, reformulated and alternate drilling muds were examined in Phase 2, and there was a positive impact upon both filtrate loss and permeability, although the Nano-CT quantifications and visualisations showed that drilling mud constituents were still having an impact upon permeability. Candidate treatment fluids were examined in Phase 3, with all having a positive impact and the best performance coming from 15% HCl and an enzyme-based treatment. The interpretative tools showed that these treatments had removed drilling mud-cakes, created wormholes, and bypassed the areas where constituents were retained. The compatibility corefloods on tight reservoir core, alongside high-resolution quantifications and visualisations, therefore identified damaging mechanisms, helped identify potential to improve hydrocarbon recovery, and identify treatment fluid options which could be used in the fields.
Deployment of State-of-the-Art Horizontal Pumping System HPS Technology in Two Water Wells to Avoid ESP Workovers
Authors: Alrabeh Majed Nahed , Samsudine Zulkiflie Bin , Ruvalcaba Velarde Salvador Alejandro , Alhajri Faisal Mohammed
Published: December 2021

The objective of this paper is to present the findings obtained from a detailed engineering evaluation resulting from trial testing two state-of-the-art surface horizontal pumping systems (HPS's) in two water supply wells. The two horizontal pumping systems were deployed as an alternative to downhole electrical submersible pumps (ESPs) to provide the benefits of eliminating ESP workover costs, modularity regarding wellsite deployments, and enhanced maintenance operations.

For this trial test evaluation method, two HPS's were deployed to boost water production to the water injection plant (WIP). To ensure a thorough evaluation, the trial test well candidates were designed to accommodate both a subsurface ESP as well as a surface HPS to provide an accurate comparison, and representation, between the different artificial lift methods. The trial test and comparison method described in this paper focused primarily on the following items; maintenance and well intervention requirements, evaluation of operational availability, including potential for cavitation and effects of interference, maximum production rates, as well as root cause engineering evaluations for mechanical seals and cooling unit auxiliary motors. Various best practices and mitigation measures were identified and are presented in this paper.

With regard to the results, it was observed that each artificial lift method comprised a set of advantages and disadvantages. The decision on which type of technology to use can be dependent on several factors. Overall, the HPS's demonstrated the ability to supply water production to the WIP. The HPS did experience operational challenges in providing higher production requirements. Additional challenges were also observed in the sealing mechanism as well as the auxiliary cooling unit. Precautionary pump tripping automated protocols were taken to prevent pump cavitation due to sub-optimal intake pressure resulting from possible interference. The HPS, unlike the ESPs, did not require any workover as it is located at the wellsite and therefore resulted in substantial cost savings and was easy to maintain due to its surface application.

In summary, this paper adds a new and very beneficial evaluation of HPS's, and highlights best practices and lessons learned to the existing body of literature. The new information discussed in this paper is highly beneficial to engineering selections of artificial lift methods and to the successful implementation of HPS's in the industry.
Boosting Gas Processing Energy Efficiency by Waste Heat Recovery
Authors: Al Ketbi Waneya Abdulla , Sajjad Saqib , Al Jenaibi Eisa Salem
Published: December 2021

A continual improvement in energy efficiency of existing plants is imperative to achieve ADNOC target to reduce greenhouse gas emissions (GHG) intensity of operations by 25% in year 2030. The waste heat recovery (WHR) from incinerator stacks of existing Sulphur Recovery Units (SRUs) in ADNOC Gas Processing exhibits a substantial potential & contributor of energy savings and emission abatement. A high level assessment was carried out for various heat sources, results showed substantial WHR potential can be availed from SRUs. Consequently, a feasibility study was carried out to evaluate several options to recover energy from incinerator stacks of existing Sulphur Recovery Units (SRUs). The feasibility study addressed three options of recovering energy from SRUs incinerator stack exhaust; generating saturated steam, generating power and combined solution of steam & power. Those options were assessed in terms of technical feasibility and commercial viability.

The study indicated that steam generation by HRSGs is technically viable and economically feasible, and considered as the best option for WHR from the existing SRU Incinerator Stacks. The WHR benefits that can be realized from just one incinerator stack by recovering the waste heat and reducing the flue gas temperature by 400 °C only (from 700 to 300 °C) are: More than 80 TPH saturated HP steam generationFuel gas savings and corresponding monetary benefitsSignificant abatement in GHG emissions

The study revealed that WHR does not pose acid condensation risk due to the safe margin between the acid dew point and the actual flue gas temperature. The study also established that other constraints like pressure drop, space, tie-in location and emissions dispersion are not the showstoppers.
Developing Next Generation Petrotechnical Professionals in the Age of AI
Authors: Agbaji Armstrong Lee
Published: December 2021

The most common challenge facing the oil industry in the Age of AI is talent scarcity. As digital transformation continues to redefine what it takes to work in the industry, staying relevant in the industry will require knowledge and understanding of the underlying technologies driving this transformation. It also requires a re-evaluation of how next generation petrotechnical professionals are nurtured, educated, and trained. The human talent that is needed in the Age of AI is different, and simply obtaining a science or engineering degree will no longer suffice to survive and thrive in the industry. While it is vitally important that students continue to take fundamental engineering and science courses and learn industry-specific skills, we must recognize when an existing curriculum or way of teaching and learning has either run its course or has evolved.

This paper examines how artificial intelligence will impact the training and development of the industry's future workforce and what organizations must do to retain existing talents while at the same time developing new ones, so they are not rendered irrelevant by AI. It proposes novel ways by which practical digital transformation and energy transition technologies can be integrated into core oil and gas education and training curriculum. It also outlines various innovative ways that academic institutions can join forces with industry to educate and train technical professionals, who, right out of college are sufficiently grounded to analyze, evaluate, and communicate data findings to drive better business decisions. For students and young professionals, it lays out the roadmap to readiness, and how to thrive in a digitally transformed world, as well as several ways to robot-proof their career and stay ahead of the curve.

The task of training industry leaders of the future is enormous, sensitive, and demanding. The ability of next generation petrotechnical professionals to succeed in the digital age, and compete in a data-centric world, depends on their ability to develop, adopt, and apply next generation skills. Having the right mix of skills is not only essential to their success, it is critical to the survival of the industry. In the Age of AI, classroom learning needs to be deemphasized and experiential learning needs to be emphasized.

The workforce of the future will be dominated by people with analytics skills and capabilities. Preparing next generation professionals for the future of work calls for a re-evaluation, re-design and recasting of the synergy between academia and industry. Universities and industry will need to routinely intersect to create symbiosis and enhance our educational system. Success will depend on sustained partnership and collaboration, not merely shifting the problem to one another.
An ESP Production Optimization Algorithm Applied to Unconventional Wells
Authors: Bermudez Fernando , Al Nahhas Noor , Yazdani Hafsa , LeTan Michael , Shono Mohammed
Published: December 2021

The objectives and Scope is to evaluate the feasibility of a Production Maximization algorithm for ESPs on unconventional wells using projected operating conditions instead of current ones, which authors expect will be crucial in adjusting the well deliverability to optimum frequencies on the rapidly changing conditions of tight oil wells.

Actual production data for an unconventional well was used, covering from the start of Natural Flow production up to 120 days afterwards. Simulating what the production would be if a VFD running on IMP Optimization algorithms had been installed, new values for well flowing pressures were calculated, daily production scenarios were evaluated, and recommended operating frequencies were plotted.

Result, observations, and conclusions:

A. Using the Intelligent Maximum Production (IMP) algorithm allows maximum production from tight oil wells during the initial high production stage, and the prevention of gas-locking at later stages when gas production increases.

B. The adjustment of frequency at later stages for GOR wells is key to maintaining maximum production while controlling free gas at the intake when compared against controlling the surface choke.

Novel/additive information:

The use of Electrical Submersible Pumps for the production of unconventional wells paired with the use of a VFD and properly designed control algorithms allows faster recovery of investment by pumping maximum allowable daily rates while constraining detrimental conditions such as free gas at the intake.
Unlocking the Potential of Electrical Submersible Pumps: The Successful Testing and Deployment of a Real-Time Artificially Intelligent System, for Failure Prediction, Run Life Extension, and Production Optimization
Authors: Bermudez Fernando , Al Nahhas Noor , Yazdani Hafsa , LeTan Michael , Shono Mohammed
Published: December 2021

This paper is a summary of the collaborative work between a Gulf Cooperation Council (GCC) national oil company (NOC) and Nybl, a deep tech development company, and the results of applying Nybl's proprietary science-based AI to the GCC NOC ESP wells in real-time applications. The paper demonstrates the potential benefits of the real-life application of AI / Machine Learning in conjunction with traditional Petroleum Engineering concepts and algorithms to predict imminent and future failures, extend and monitor run life, and maximize the production of Electrical Submersible Pumps (ESP's). This paper will highlight the NOC's innovative approach to pilot new technology through successful deployment on 27 wells, spread onshore and offshore, in real-time, with prescriptive actions.
Acoustic MEMS Transducers: Look Ahead of the Bit and Geopressure Monitoring
Authors: Turolla Axel , Zampato Massimo , Carminati Stefano , Ferrara Paolo
Published: December 2021

This paper describes the design and implementation of Acoustic Micro Electro Mechanical Systems (hereinafter referred to asA-MEMS)working in fluid-coupling mode for HP/HT specifications relevant to downhole applications such as drilling, well and reservoir monitoring. Many cutting edges applications ofA-MEMS in Oil & Gas industry are envisaged. The current work refers to the case study of a "Look Ahead of the Bit"/geopressure monitoring technique (hereinafter referred to asPPM) developed by the authors.

A–MEMS with magnetic shuttle transducers have been designed so that they are not affected by environmental pressure like piezoelectric devices commonly used in MWD commercial sonic tools, which are impaired by volumetric shrinking/expansion working principle. This performance is also achieved by embedding an environmental pressure compensator tuned in the whole working bandwidth to grant pressure balance even with oscillatory motion at sonic frequencies (up to 5 kHz). Transmitter acoustic power and receiver sensitivity have been optimized in a bandwidth between 500 and 3500 Hz.

A couple of A–MEMS prototypes have been built and successfully tested by using an oil filled pressure vessel at downhole T–P conditions (200 °C, 700bar) and an ad-hoc measurement setup including force, displacement, temperature sensors, transmitter (TX) driver, receiver (RX) lock-in amplifier and anacquisition system. Moreover, modal analysis at typical drilling conditions has been carried out by Stewart platform. Shock up to 1000 g and random vibrations up to 12 g RMS in 5 ÷400 Hz bandwidth have been tested. A–MEMS performance have turned out to be consistent with theoretical model predictions andhave exhibited robustness to T P variations and applied structural stress.

PPM method has been validated through a triaxial compression cell in a rock mechanics laboratory, implementing a lab scale scenario with a cap rock located above a permeable rock, undergoing all geopressures of interest. However, piezo transducers used in the experiment underwent a significant failure/damage rate along with performance degrading at pressure increasing. These observations confirmed and motivated the need for A-MEMS technology development in downhole applications.
Enhancing Operational Safety Through Mechanization and Intelligent Automation of Drill Floor Operations
Authors: Mwansa Peter Levison , Varma Esha Narendra , Grayson Paul , Norton Justin , Webber Daniel , Ligardo Emmanuel
Published: December 2021

Our rig crews regularly work around structures that pose risks such as dropped objects and pinch points. HSE and operational performance is highly dependent on human performance. Human performance or human factors have resulted in a relatively high frequency of serious Health, Safety and Environment (HSE) incidents associated with tubular handling on ADNOC Onshore rigs. An example is the fatality on a rig in Abu Dhabi while preparing to run casing in February 2018.

We believe we can prevent major incidents, enhance efficiency and reduce risk by removing our people from harm's way through mechanization and intelligent automation of drill floor activities. The objective of this work is to reduce the human factor as low as reasonably practicable through mechanization and intelligent automation of tubular handling operations on ADNOC Onshore rigs.

An incident prevention workshop recommended a technology search to enable hands free operations and reduce the human to machine interaction as much as reasonably practicable. A quick market research and a "Go, See, Assess" exercise with ADNOC Shareholders revealed several potential offerings on the market. ADNOC Onshore collaborated with two major technology providers and jointly designed a mechanized set up for ADNOC Onshore land rigs. The solution involved the use of mechanized equipment such as Casing Running Tools complete with hydraulically actuated single joint elevators, hydraulic catwalk, automated power slips, remote operated tong system with supporting alignment systems, air operated elevators, remote operated stabber, etc.

The solution was successfully implemented on multiple rigs. The mechanized set up reduced the number of people in the so called RED Zone by 50% (Stabber, Tong Operator, Thread Inspector and Floor man) during casing and completion running operations. Other benefits realized include:

Reduced reliance on human performance Reduced risk of harm to people due to dropped objects and pinch points on the rig floor Assured consistency in executing repetitive tasks such as running casing, etc

This level of mechanization and intelligent automation is a first in the ADNOC Group, represents a STEP CHANGE in operational safety and has transformed how we do our business, underpinning HSE as priority number one.
Maximizing Production by Perforating with Accurate Dynamic Underbalance Using Electric Coiled Tubing Offshore Egypt
Authors: Ghonim Ahmed ElSayed , Elfarran Amr Zeinhom , Okasha Osama Aly , Haridy Ehab Mohamed , Koriesh Mahmoud Mohamed , Mousa Aly ElBasyouni , AbdelSabor Ahmed Gaber
Published: December 2021

This paper represents a challenging rig-less intervention in highly deviated wells with heavy oil that has always been a challenge to conventional electric line (e-line) that is not a valid intervention technique due to its inherent limitations in these harsh environments. Electric Coiled Tubing (E-CT) was utilized not only to achieve safer deployment of the guns, but also to allow real-time operations on three wells which were inaccessible due to heavy oil content and restricted e-line accessibility.

A case study is presented for a campaign performed using E-CT to convey the perforating string while pumping nitrogen (N2) to lift the well and achieve flowing under-balance to maximize perforation clean-up and minimize skin. Real-time readings from gamma ray, pressure and temperature sensors were used to accurately position the guns, generate the desired dynamic underbalance, and finally validate successful detonation based on pressure and temperature responses. This was achieved while N2 lifting and firing the guns to optimize the required under-balance value providing immediate feedback related to the production gain to determine the zonal contributions and maximize the economical production gains. Dynamic wellbore behavior software modeling was also used to predict the dynamic under-balance effect for maximizing perforation efficiency.

Deployment of E-CT was very challenging in terms of operational execution but was extremely beneficial for the safety of the pipe during such operations. A total of 13 runs comprising of milling, tubing cleaning and drifting were performed to remove the accumulated scales inside the production tubing and to ensure full accessibility to target intervals. Coiled Tubing (CT) dynamic modeling software was utilized to simulate the N2 rate needed to achieve the target underbalance while maintaining safe perforating parameters for the CT while firing the guns. As a result of software simulations, one of the three wells was then recommended for an acid wash treatment which achieved very effective results.

15 perforation runs were performed on the three wells re-perforating a total of 188 ft of interval, resulting in a production increase of more than 300%. This was a significant improvement compared to the previous campaign carried out in 2017 where perforating in static conditions showed no increase in production without work-over rig intervention. E-CT intervention also eliminated the need for waiting on rig schedule and avoiding deferred production.
Development of a Digital ESP Performance Monitoring System Based on Artificial Intelligence
Authors: Diker Göktug , Frühbauer Herwig , Bisso Bi Mba Edna Michelle
Published: December 2021

Wintershall Dea is developing together with partners a digital system to monitor and optimize electrical submersible pump (ESP) performance based on the data from Mittelplate oil field. This tool is using machine learning (ML) models which are fed by historic data and will notify engineers and operators when operating conditions are trending beyond the operating envelope, which enables an operator to mitigate upcoming performance problems. In addition to traditional engineering methods, such a system will capture knowledge by continuous improvement based on ML.

With this approach the engineer has a system at hand to support the day-to-day work. Manual monitoring and on demand investigations are now backed up by an intelligent system which permanently monitors the equipment. In order to create such a system, a proof of concept (PoC) study has been initiated with industry partners and data scientists to evaluate historic events, which are used to train the ML-systems.

This phase aims to better understand the capabilities of machine learning and data science in the subsurface domain as well as to build up trust for the engineers with such systems.

The concept evaluation has shown that the intensive collaboration between engineers and data scientist is essential. A continuous and structured exchange between engineering and data science resulted in a mutual developed product, which fits the engineer's needs based on the technical capabilities and limits set by ML-models. To organize such a development, new project management elements like agile working methods, sprints and scrum methods were utilized.

During the development Wintershall Dea has partnered with two organizations. One has a pure data science background and the other one was the data science team of the ESP manufacturer.

After the PoC period the following conclusions can be derived: (1) data quality and format is key to success; (2) detailed knowledge of the equipment speeds up the development and the quality of the results; (3) high model accuracy requires a high number of events in the training dataset.

The overall conclusion of this PoC is that the collaboration between engineers and data scientists, fostered by the agile project management toolkit and suitable datasets, leads to a successful development. Even when the limits of the ML-algorithms are hit, the model forecast, in combination with traditional engineering methods, adds significant value to the ESP performance.

The novelty of such a system is that the production engineer will be supported by trusted ML-models and digital systems. This system in combination with the traditional engineering tools improves monitoring of the equipment and taking decisions leading to increased equipment performance.
Managed Pressure Drilling and Underbalanced Drilling Compounded Role in Solving the Exploration and Appraisal Challenges of Biogenetic Gas Resources in the United Arab Emirates -Case Study
Authors: Al Mutawa Ahmed , Hamdy Ibrahim , Al Shamisi Eias Daban , El Yossef Bassem , Amin Mohamed Sameer , Nunez Ygnacio , Saleh Mujahed , Hadj-Moussa Ayoub
Published: December 2021

Biogenic gas resources have gathered importance recently due to its widespread availability, occurrence at geologically predictable circumstances, and existence at shallow depths. It is estimated that biogenic gas forms more than 20% of the global discovered reserves. However, the exploration and development of these unconventional resources come with numerous drilling and reservoir challenges. This paper showcases a novel approach used in the United Arab Emirates to overcome these challenges using managed pressure and underbalanced drilling.

To tackle both reservoir and drilling challenges, a hybrid solution combining Underbalanced (UBD) and Managed Pressure Drilling (MPD) was applied. UBD was used to characterize the reservoir in terms of pressure and productivity index to ultimately enhance productivity by eliminating formation damage. MPD was used next to continue drilling through the problematic zone which had high instability due to the presence of highly sensitive salt, in addition to the presence of high pressure and loss zones. The fit for purpose hybrid application design allowed the operator to immediately switch between UBD and MPD conditions, as the well required with the same equipment.

Three of the four targeted formations were in the 8 ½″ hole section, UBD was selected to drill the first reservoir formation which allowed pore pressure verification and avoided using excessive mud weight that was the culprit of many challenges like slow ROP, drilling fluid losses, bit balling, and fracking the formations. UBD has proved that mud weight can be reduced by 20%-30% comparing to conventional drilling. The second formation was a salt formation that has caused previously hole collapse and losses-kicks problems as heavy mud used to drill this salty formation. MPD used successfully drill this section by constant bottom hole pressure and lower mud weight as it was found from analyzing offset wells reports that hole collapse occurred at connections and pump off events. Constant Bottom Hole Pressure (CBHP) also eliminated tight spots and excessive reaming resulting in optimized drilling. The third formation used MPD as well to minimize overbalance pressure over previous sections while the fourth formation was drilled by UBD as it had a separate 6″ hole section as it formed an independent reservoir.

The combined MPD and UBD approach eliminated most the NPT encountered in offset wells, enhanced Rate of Penetration (ROP) by 200% to 300% and slashed the well drilling time by 27 days.
The Future of Learning
Authors: Cesaro Mario
Published: December 2021

The unexpected discomfort caused by Covid-19 pandemic and all the consequent government restrictions on travels and social distancing have pushed all the Training Organizations worldwide into an unusual challenge, being forced to support their Customers from afar.

This work aims to thoroughly analyze the success of the Remote Learning methodology, highlighting key factors impacting the learning curve, and to share effective improvement ideas for this approach to deliver training focused on technical and human skills.

Many companies reacted to this situation by investing largely in and increasing the adoption of digital technologies to facilitate internal and external communications and more specifically to support Remote Learning. However, despite the prompt response, many Training Organizations found themselves delivering their products through a series of trials, mistakes and lesson learned on methodology and tools.

The detection of few but significant improvements increased effectiveness and improved interaction in our Remote Classes. The improvement actions concerned learning how to make the most of the available digital technologies and identifying the most effective applications for sharing documents and interacting with participants; at the same time, a great focus on the human skills approach was crucial to learn how to promote trust, motivation and interaction between our staff and Customers’ personnel.

In this perspective, Operator Training Simulations (OTS) and Remote VR Training have emerged as one of the best applications to increase the attendees’ learning curve and help develop Customers’ personnel skills.

Our study, however, isn't all about bright stars. The feedback told us that some Customers still prefer to take in-person training classes rather than remote ones. Sometimes this relates with biases against remote or digital activities, but it often applies where hard activities need to be performed.
Maximizing Condensate Production Opportunities in a Giant Stacked Reservoir-Case Study
Authors: Al Agbari Zainah Salem , Al Yaaquibi Nouf Sulaiman , Sudarev Maxim , Mohamed Ihab Nabil , Al Hosani Mariam Ahmed , Latypov Eduard , Al Bairaq Ahmed Mohammed
Published: December 2021

This paper addresses the opportunities of maximizing the condensate production in a giant Recycle Gas-Condensate Reservoir in UAE. The condensate reservoir is producing many years under recycling mode to maintain the pressure and maximize the gas condensate recovery. The producers and injector wells are in a line drive pattern where the injected fluid is lean gas to maintain 100% VRR. The condensate production declined through the years due to gradual pressure decrease as well as injected lean gas/N2 breakthrough. Several studies were done to increase condensate recovery and extend gas production plateau.
Achieving Operational Efficiencies from a Centralized Alarm Management System
Authors: Al Mahmoud Mahmoud AbdulHameed , David Joseph Sylvester Pius , Jaffer Askar
Published: December 2021

Alarm Management Systems ("AMS") have been adopted in the oil & gas industry where several benefits were realized. Such as improved panel operator effectiveness, maintaining higher levels of plant uptime and integrity, reducing the number of abnormal situation. Which ultimately leads to higher asset productivity.

Several OPCO have multiple operational assets/sites that are geographically diverse. Where each asset might have a different Integrated Control System ("ICS") due to the time and availability of technology at the time of commissioning. Requiring diverse locally implemented AMS.

A unified CAMS thus reduces time and effort to develop, deploy, and maintain alarm systems and is an essential toolkit for enhanced safe operation of the plant.

Some sites have multiple plants wuth common pocess control section. The process control enginners needs to visit individual plants access DCS alalrms. By carryinhour corporate alarm management, engibbers at their office PCs have the access to the DCS alarms.

Implementing CAMS requires the presence of a robust data presence infrastructure in place. Notably a centralized plant information management system, where several real time data points with regards to alarms and operator inputs can be captured.

A CAMS unifies the approach of how alarm management is conducted in the company. Where a CAMS system generates a set of standard and custom templates that highlight the performance of each operating asset/shift/panel operator. Providing insights into the performance of each asset, efficiency of each operational shift and response of the panel operators. That when addressed, will lead to an overall performance and production of the operational asset.

With this alarm management data, it can be further enhanced through data analytics to identify areas where operational efficiencies can be achieved. Additionally, the CAMS reduces the times and effort to deploy an alarm management system for any future operating asset expansions.

CAMS coupled with real time data and Machine learning algorithms, past behaviours of the plant can be correlated, which can then be utilised for future predictions on alarms. This would further enhance our data driven decision-making, and would reduce the dependence on personal driven decisions.

It can be concluded, that the CAMS is worthy investment for operating companies that have geographical/ICS diverse operational assets.