bluuebunny/crossref_metadata_2025 huggingface dataset:
Model Approach to Achieve Zero Methane Emissions Contributing to Global Methane Pledge
Authors: Vaswani Y. , Al Kamali O. , Rasulova Z. , Al Ameri S. , Almemari F.
Published: October 2023

Abu Dhabi National Oil Company (ADNOC) announced a new Upstream Methane Intensity target of 0.15% by 2025. The new target is the lowest in the Middle East, reinforcing ADNOC's status as a responsible producer of lower carbon intensity energy.

At ADNOC, our aim is to reduce the methane intensity from our operated oil and gas assets, while ensuring energy security and meeting the energy demand. We are achieving this by improving our methane monitoring and reporting, making significant investments in new technologies to improve our environmental performance, thus support UAE's Global Methane Pledge.

The target of 0.15% methane intensity reflects industry best practices that report total volume of upstream methane emissions from all operated upstream oil and gas assets and where emissions intensity is calculated as a percentage of the volume of total gas marketed for the same upstream sector.

A detailed gap analysis was conducted to review the relevant documents, including but not limited to emission inventory & records, materiality analysis, emission sources inventory etc. to identify the gaps and developed the action plan for achieving the Gold Standard. Accordingly, inventory was developed, Leak Detection & Repair program implemented, flaring emissions minimized, Combustion Efficiency is being monitored and improve

ADNOC Onshore also used satellite monitoring data to track the emissions across its operation.

Since the operation is spread over the large area so it was a real challenge to monitor all the sources of emissions. Hence, support was acquired from all the stakeholders, shareholders, business partners to achieve the common goal.

After the implementation of all the actions, methane emissions intensity of 0.09% for the year 2022 was achieved, which is below the ADNOC target of 0.15% by 2025.

The present publication introduces a model approach to achieve zero methane emissions, which can then be used by upstream companies to develop and implement action plan to achieve methane reduction target.
Optimizing Well Placement in a Complex Reservoir: A North Sea Case Study of World First Utilization of Latest Surveying and Geosteering Technologies in Drilling Operations
Authors: Fawzy M. G. , Hassan H. K. , ELSedeq A. Z. , Nketah D. N. , Uzuegbu E. , Kumar D. , Castagnoli J. P. , Vliet Rutger V. D.
Published: October 2023

State-of-the-art measurement-while-drilling (MWD) directional surveying coupled with the latest 3D reservoir mapping technology were run simultaneously for the first time globally in the North Sea, Norwegian sector. The goal of the project was to bring unparalleled value to the Operator’s development campaign in the complex reservoir structure of the Duva field in the northern part of the North Sea.
Streamlining Information Retrieval Using a Chatbot Application
Authors: Sittipolkul N. , Wanwilairat S. , Sujijintararat K.
Published: October 2023

Objective

Wellhead Platform Department has engineered and installed more than 100 remote wellhead platforms (WHP) and pipelines for the past decades. Information of each different design WHP is kept in shared folder in case later generations have to modify/maintenance WHP. However, with hundreds of documents per each WHP, sometimes it takes more than hours to find all the required information. Thus, our team developed Chatbot to help find information to respond to repetitive and time-consuming questions.

Method and Procedure

Utilization of chatbot has garnered popularity over the recent year. With that opportunity, information finding could be easier by adopting this technology to develop in-house chatbot application. The database scope covers offshore WHP and intra-field pipelines. Google Dialogflow was used as a natural language processor from queries made via Microsoft Teams. As for backend service, python scripts and BigQuery were used to convert data to an appropriate database format and gather information from pre-populated Excel files to respond to fulfilment requests from Dialogflow. The conversation history and users tracking were available in web base for the purpose of training chatbot.

Results, Observation and Conclusions

By employing the in-house chatbot application, the results from web-based historical conversation data showed that this chatbot application effectively cut down the time wellhead platforms engineers spent on looking up for information and respond to routine questions, which in turn allows the engineers to focus on more critical tasks. Moreover, instead of having to ask for information from wellhead platform team, users can reach out to information and document through chatbot application 24/7. However, current problems mostly lie with the engineers still having to manually creating a data set in a format that backend services can recognize and make use of. Nevertheless, using the chatbot is an efficient mean to handle tedious inquiries which improves inquiry workflow and eventually saves valuable time and resources.

Novel

This paper presents a novel information by demonstrating the use of a chatbot in oil and gas industry which can be extended to any other field, given that the database is readily available in a format acceptable to the programs. The application was developed by Engineering team of Wellhead Platform Department (EWP) together with Data Scientist and Data Architecture of Digital Solution Development Section.
Critical Evaluation of Sustainable Local Content Policy in Nigeria Oil and Gas Sector
Authors: Biragbara Neeka Jacob , Adaure Prince Favour , Lemuel NuBari
Published: October 2023

A study of the role of sustainable local content policy in human capacity development in Nigeria’s oil and gas industry – case for the Petroleum Technology Development Fund (PTDF, the Fund) was carried out to find solutions to three fundamental questions: "to what extent has PTDF contributed towards achieving human capacity development in Nigeria" "to what extent has PTDF intervention impacted the oil and gas industry in the last ten years in Nigeria" and "how sustainable is local content policy under the present PTDF mandate in Nigeria". This research was predicated on the skills gap audit report (2018 – 2023) of the Fund as a baseline study while leveraging on the secondary data sets of the PTDF trio-capacity development strategies from 2011 – 2021. The research was formulated on both descriptive and analytical statistics methods based on the industry need assessment. A comparative analysis of the Skills Gap Audits (SGA) and Secondary Data Sets (SDS) was carried out using arithmetic mean and deviation from the assumed mean of the unclassified data. The results established that more key performance indicators were captured in the SDS (mean of 23.04 and deviation of 0.4) against the imputed values in the SGA (mean 4.52 and deviation of 0.5 respectively). The implication therefore is that PTDF has contributed more significantly in human capacity development programmes than indicated in the SGA report. However, challenging indicators could be turned into opportunities if the extant law is amended to broaden the frontiers of investment-divestment strategies through public-private partnership for sustainable local content policy of the Fund. This research is useful for policy formulation and decision-making on local content in Nigeria.
Zero-Flaring Technique to Boost Low Pressure Oil Wells Production and Revive Dead Wells Through Multiphase Ejectors
Authors: Alzaher H. D. , Mulhim A. A.
Published: October 2023

Saudi Aramco, as the world's leader in energy supply, spares no effort to explore innovative approaches and techniques to ensure a sufficient supply of energy to the world. This arises while ensuring to manage the carbon footprint that will be resulted oil production, and to maximize the value creation from the operating facilities. This also includes the relentless efforts to unlock the full potential of the Kingdom's resources. Therefore, Saudi Aramco strives to reduce flaring and minimize carbon footprint at its premises. In spite of all the exerted efforts, strict policies, challenging targets and investments to achieve a continual improvement in environment protection, it would be hard to avoid a performance plateau without breakthrough solutions. This is particularly true in Saudi Aramco, considering the large geographical area in which different facilities are scattered.

In addition, environment protection and flaring reduction is an increasingly important topic that needs to be considered today more than ever to minimize the side effects of our operation in order to achieve circular carbon economy and net zero. One of the best areas to protect our environment at industrial facilities is to minimize flaring during our normal operation. This is especially if flaring in correlated to some mode of operation that will entail production and wells performance.
AI-Enhanced Tools for Performance Enhancement in Energy and Water Systems
Authors: Kobayashi Dylan , Arumugam Ganesh , Kimura Mark , Nakatsuka Matthew , Taketa-Tran Jasmine , Thapa Sumil , Veedu Vinod , Ventura Alexander
Published: October 2023

Whether used for transportation of gas, oil, produced water, or wastewater, pipeline infrastructure is critical to many industries and is the most effective way to transport large quantities of fluids and gases. Considering that that large portions of pipelines are increasingly reaching or exceeding their service lifetimes, technologies that help with maintenance and extension of service life are a critical future need. One increasingly popular method of improving performance and reducing maintenance requirements are utilizing internal surface application of coatings and surface treatments to reduce the chance of deposits and the formation of corrosion. Proper coating and application require careful surface preparation to minimize the risk of coating adhesion failure and catastrophic delamination. The natural variation in training and experience of applicators can often lead to quality control issues for coating, and on system performance and expected lifetime. Utilizing a disruptive application of artificial intelligence to reduce subjectivity and reliance on operator interpretation can thus enable a more systemically uniform method of achieving quality control goals, while additionally making the process of coating and surface treatment more efficient.

This work describes a novel approach to combine a digital inspection system with artificial intelligence (AI) to identify defects and areas of risk in existing pipelines to assist with coating application quality control. Video captured from borescopes and pipeline inspection gauges (PIGs) were supplemented with sensor data for an AI to utilize for evaluation of coating quality and coverage. A two-step approach was followed, whereby transforms and training took place on small diameter pipes and using the algorithm with a pig-mounted capture tool. The inspection method transforms videos into a static two-dimensional (2D) image map that is representative of the inspected tubular being longitudinally cut and unwrapped into a flat surface, which can then be processed with the AI component to identify defects and features of interest. Applications described in this work include estimation of corrosion, cleanliness after intervention, and coating coverage after application. Additionally, the 2D generated maps were backmapped onto 3D plots to preserve the relative geometry and dimensions of the pipeline in a fully interactive virtual space which could be manipulated by a human user for further defect analysis and inspection. As a proof of concept, the AI system was trained to distinguish the level of discoloration present on steel substrates designed to imitate the interior diameter of transport pipelines. Classification accuracy was 91.2% overall when predicting for cleanliness using the AMPP standard classification system.
Transforming with Our People – Leading Business Transformation Through People Development
Authors: Ho Boon Keng , Paul Christelle Saint , Daniseviciute Giedre
Published: October 2023

TotalEnergies plays an active role in the transformation that is underway in the energy industry and the vision is to be a Carbon-Neutral Company by 2050. To attain this goal, strategic investment policy was designed to accelerate access to low-carbon solutions (electricity and renewable energies, biogas and biofuels, low carbon fuels, CCS) while continuing to meet the world's current energy demand.

As TotalEnergies enter a significant phase (Year 2020 to 2030) in the transformation into a multi-energy company, a clear business transformation roadmap has been created to transform TotalEnergies to reinvent energy. This includes the element of transforming our workforce to meet the new challenges and environment.

In 2019, "Better Together", a worldwide People Ambition project was launched, in response to employees’ expectations. The ambition has three workstreams: to develop every employee, promoting the manager-coach and to promote a positive work environment by listening to employees’ concerns. The workstreams have been translated into concrete projects, to quickly anchor the changes in the daily lives of employees. More than 400 talent developers (TDs) are actively working closely with employees, to provide each employee individualized support and career coaching. There is also a revamp in the internal mobility process to provide more support and transparency for employees in the internal recruitment process. More than 35 000 vacancies have been published on an internal Job Posting platform since the introduction of Better Together in 2019.

Job mobility (functional and geographical) and continuous training are essential levers to develop everyone's skills and employability. These allowed our talents to develop the skills that is relevant to the changing business challenges. Managers are also empowered and trained in their role as manager-coaches, to support team development. This is a significant step to changing the managerial culture as we move to a more collaborative approach of management.

To support employees in this transformation, Transforming with our People program was launched in 2022 as part of the evolution of Better Together ambition. A program for supporting our teams through the transformation, it has three major workstreams: "Listening", "Informing", "Learning" and an additional workstream for young people at TotalEnergies, providing everybody with an opportunity to learn about and buy into TotalEnergies’ ambition, to develop and learn new skills, establishing a broad-energy culture. The goal is to be part of the energy transition, a fair transition for everyone.

TotalEnergies People Ambition encompasses a holistic approach covering topics like employee engagement, developing talents, promoting diversity & inclusion, and well-being of employees. This proposed paper focuses on the People Development principles and initiatives adopted to drive the transformation.
A Unique Development Model for Paraprofessionals at Engineering Organization
Authors: Al-Qarni Hassan Saeed
Published: October 2023

This paper presents a successful human resources development model for paraprofessional personnel in an engineering entity. A healthy organization must sustain reliable workforce through comprehensive and well-structured development. A development program for Engineering Aides (EA) and Assistant Engineers (AE) was mandated to ensure progressive development throughout paraprofessional career life. The main objective of the program is to foster knowledge of paraprofessionals through proper integration between soft skills and technical engineering concepts in a steady and efficient manner. In addition to the knowledge building process, an administrative structure has been introduced to ensure proper governance of the program as well as sustain progression and alignment to the organizational strategy towards human resources development.
Large Language Models Trained on Equipment Maintenance Text
Authors: Abijith P Y , Patidar Piyush , Nair Gaurav , Pandya Rohan
Published: October 2023

Work orders, equipment information, technical records and best practices documents contain within them a wealth of insights related to Equipment Maintenance which can be unlocked with Natural Language Processing tasks like classification, clustering, named entity recognition or part of speech tagging. But obtaining large enough labelled data sets in Equipment Maintenance domain manually is prohibitive and very expensive. This lack of labeled Equipment Maintenance data can be overcome with Large Language Models (LLMs) such as GPT-3, BERT that are pretrained transformer networks, considered state-of-the-art when it comes to Natural Language Processing (NLP) tasks. However, the vocabulary understood by these LLMs are mostly from English Language and need to be fine-tuned to understand industry and organization specific vocabulary and acronyms.

This paper explores the potential of a domain specific LLM model for oil and gas industries. Data that are of good quality and that provide a comprehensive overview of industry are collected. This corpus of text contains documents like work orders, equipment data and technical documents. A custom tokenizer is trained on this data to identify domain specific terminology. A comparative study is done with other off-the-shelf tokenizers: BERT and RoBERTa, to compare the effectiveness of the tokenization.

With millions of work orders and equipment documents, training pipelines had to parallelized so that training can occur on multiple GPUs. A comprehensive study of multiple training methods is done in this paper. Model and tokenizer developed were packaged and archived to be consumed in machine learning pipelines to specific use-cases across the organization. For an organization adopting digital transformation, the availability of an organization specific LLM is an enabler to extract insights from millions of documents containing free text. The applicability of such models spans across multiple disciplines like Maintenance, Reliability, Safety etc. and streamlines the development of highly accurate and robust text analytics.
Prescriptive Analytics of a Surface Safety Valve at the Edge
Authors: Gharib H. , Whitehead M. , Chin M. , Flesher H.
Published: October 2023

A Surface Safety Valve (SSV) on wellheads and flow lines is the last line of defense to protect personnel, environment, and assets from potential catastrophic damages. With the rising demand to reduce greenhouse gases (GHG), spills, and limit operational footprints, digital transformation combined with electrification and smart algorithms are critical steps towards achieving this goal.

This paper presents the recent development of a surface safety valve (SSV) controlled by an IOT-based smart emergency shutdown (ESD) system that integrates, at the wellhead, an electro-hydraulic power unit with control elements, sensors, edge computer/controller, and remote connectivity in a hybrid edge-cloud platform. Real-time data from position, pressure, and temperature sensors digitally transform the SSV and are used to feed the diagnostic algorithms. In addition to triggering an ESD event, these algorithms monitor the condition of the SSV and control circuit. This is conducted through coupling the real-time processed data with physics-based models to evaluate the SSV system health.

Evaluation of the SSV and smart ESD system performance was conducted using a laboratory test unit and the major components were field tested. Sensors and control elements data was processed into three primary sets of key performance indicators (KPIs): valve health, hydraulic circuit and actuation health, and hydraulic leakage detection. The effect of varying the process line pressure on the valve signature was evaluated and compared to the available physics-based models, which showed close correlation. Moreover, coupling of the experimental data with the physics-based models was able to solve for the individual thrust load components including valve gate drag, stem force, friction, and spring pre-load from the total measured pressure. The response time during SSV closing or partial stroking was evaluated at incremental time steps to identify the source of potential malfunction in the control circuit and SSV. An emulation of hydraulic leakage revealed distinctive pressure signatures between the low- and high-pressure circuits, thus identifying the location of the leakage in the hydraulic circuit. This allows locating the exact source of malfunction in the SSV, while running prescriptive analytics to suggest component specific corrective actions.

Most of the published SSV condition monitoring efforts focus on the process valve health with less attention to the hydraulic circuit, which is a critical element of the overall SSV reliability and performance. The presented smart ESD system bridges this gap by digitally transforming the SSV to provide prescriptive analytics not only to process valve components, but also the hydraulic circuit and actuator components.
De-Manning Offshore Operations and Reducing Carbon Emissions with Autonomous Subsea Drones
Authors: Cavallini F. , Massari G. , Nevoso C. , Quick A. , Alexander T.
Published: October 2023

At the conclusion of a long and exhaustive in-shore and field-testing programme, leading to commercial readiness, this paper presents the latest state-of-the-art developments in autonomous asset integrity inspection for subsea pipelines and structures by means of autonomous subsea drone. Further, the paper reviews and provides analysis of the benefits of such technology to operators in a shallow water scenario. The presented application case, specific for the water depths that characterize the Middle East area, shows that tangible benefits can be obtained both in terms of de-manning offshore operations, reduction in carbon emissions, improvement in data quality, improved weather workability and responsiveness to urgent callouts. In particular, the existing capabilities offered by battery technologies allow a subsea operational range adequate to cover typical field layouts, with launching/recovery from a platform. Furthermore, and with specific reference to shallow water applicability, the extensive testing at Saipem premises, in 8 to 20m water depth, truly represents the ideal de-risking prior to a potential deployment in the Arabian Gulf area, having autonomous inspections as main focus. This paper presents the very latest status update for subsea autonomous and resident drone operations with data quantifying and validating the safety, carbon emissions, time-savings and cost benefits compared to conventional pipeline and subsea inspection methods, specifically for the Middle East area.
An AI-Driven Multiwell Placement and Scheduling Method
Authors: Al Tandi A. A. , Tahir S. , Elfeel M. Ahmed , Belayouni N. , Gupta D. , Ayoubi R. , Shaik I. , Hernandez C. , Su S. , Gubbala M. , Majhi S. , Rat C. , Ramatullayev S. , Mustapha H. , Amri M.
Published: October 2023

Well placement optimization is important for informed field investment decisions. Numerical simulation models are usually utilized for well placement optimization, as they offer a detailed account of subsurface reservoirs. However, a full loop optimization using numerical simulation models makes this process intractable. Instead, many assets and reservoir engineers follow heuristic or trial-and-error approaches, leading to suboptimal results. This paper introduces a novel method for well placement optimization and scheduling based on AI-proxy models.

Our approach relies on generating an Ensemble of simulation runs (100s-1000s), varying field-level and well configuration parameters. We follow a loosely coupled process to solve the field control parameters and well placement optimization problems. Output data from the field, well and completion levels are collected automatically from the simulation models. Thereafter, several Machine Learning (ML) meta-models are trained to predict field-level production, well drilling and abandonment schedules, and the performance of production and injection wells. The outcome is selected well trajectories based on opportunity maps generated using the meta-models.

The new workflow was first tested on a synthetic reservoir model. A sensitivity study of 275 simulation cases was performed varying reservoir management and well configuration parameters. It was observed that although the petrophysical properties such as rock quality and hydrocarbon saturations were not part of the ML model training, they were well reflected in the opportunity maps. This provided assurance that the model captures the basic static and dynamic controls on well performance. The model accuracy was improved further by adding features such as the perforation top depth. Additional drilling constraints, such as the presence of large faults, had to be considered to ensure the validity of the optimized well locations. The best simulation case from the sensitivity study was selected based on specific economic factors and adopted as a comparison base case for the new well optimization method. The original wells were replaced with an optimized set of well obtained with our deep learning and optimization workflow. This resulted in a 10% increase in total oil production combined with 50% decrease in the amount of water production.

Modern cloud/local computational resources can expedite full-loop optimization processes. However, both computation efficiency and elasticity do not address the iterative nature of classic well optimization methods. The method presented in this paper attempts further speedup by leveraging ML.
Future Workforce Planning - Building a Future-Ready Organization Using a Prospective Study Approach
Authors: HO Boon Keng
Published: October 2023

To stay competitive in a rapidly changing world, it is imperative to rethink the business model, workforce, and skills with the future in mind. This is a forward-looking approach to imagine the different potential scenarios of the future and use that as a frame to design the how it will impact the business.

With this ‘future’ as the vision, a back casting approach was adopted to then anticipate the changes needed today to help to transform the business successfully into the desired Future-Ready organization.

This prospective study is done based mainly on qualitative research. An external "prospectivist" (Future analyst) was engaged to work with the HR team to conduct this study. A series of external and internal research, as well as internal interviews with business leaders were conducted to imagine the potential business scenarios of the future. A backcasting strategy was then adopted to compare the current workforce and to anticipate the required evolution of the business, workforce, and competencies.

An innovative approach was adopted using big data for external competency benchmarking. Business leaders from each business were involved in the early stages from choosing the external sectors to benchmark against and the internal key jobs to be benchmarked, to reflecting collectively on the results to design action plans.

Other than the direct interventions for each business, the results were reviewed at a macro level to create a Future Workforce Plan for the organization. Further interviews and discussions with management leaders to review the key findings had created specific manpower and HR action plans to develop the workforce.

These short and mid-term action plans provide the blueprint not only for workforce planning but to set the course on developing the workforce of the future that can steer the business transformations. The scope includes identifying job evolutions, workforce reskilling and upskilling needs, potential new jobs for the future (not existent in the company) and approaches to build the workforce (external recruitment - social communities, upskilling of employees, outsourcing - gig workforce).
Production Breakthrough from Channel Fracturing: A Seven-Year Journey in South Sulige Tight Gas Field
Authors: Fuyang Wu , Qian Ma , Libin Dai , Ting Jin , Tao He , Shengfang Yang , Yu Lei , Long Wang , Yifan Dong , Qiang Wang , Na Li , Yin Luo , Liang Zhao
Published: October 2023

South Sulige Operating Company (SSOC), a joint venture company between CNPC and TotalEnergies, has been the main operator in South Sulige gas field since 2011. After years of optimization on operation parameters, the annual post-fracturing production (absolute open flow, AOF) has reached a high plateau that outperforms offset blocks. Nevertheless, because of the fast-growing domestic gas demand, utilizing proper fracturing technology to further increase production has become crucial in recent years.

This paper describes the successful design evolution of channel fracturing technology in Sulige tight gas field through a 7-year trial. Unlike the homogeneous proppant pack created in a conventional fracturing job, channel fracturing makes open and highly conductive channels by forming proppant pillars in the fracture through pumping proppant-laden fluid and proppant-free fluid intermittently. These channels are beneficial for improving effective fracture length, facilitating fracturing fluid cleanup, minimizing pressure drawdown along the fracture, and thus improving post-fracturing production performance.

In 2016, the first channel fracturing trial was conducted on four wells in this field, with comparable treatment size to conventional jobs. The average 600-day cumulative production of target wells was 25% higher than that of offset wells, which demonstrated the enhancement to effective fracture half-length and thus more fracture-reservoir contact. In 2021, the design strategy was upgraded by incorporating a more aggressive pumping schedule to improve near-wellbore fracture conductivity while reducing fracturing fluid usage, with superior production results achieved from wells with mid to high reservoir quality. In 2022, the fracturing design strategy was set to maximize the production potential for high-quality wells with increased treatment size and further extended effective fracture length. This achieved production record of 87 MMscf/d AOF from a 2-layer vertical well. This result is even comparable to performance of offset horizontal wells. Besides the promising results, through the design evolution in these 7 years, a channel fracturing candidate selection workflow with associated design strategy has been established for a similar tight gas field.

Channel fracturing has been proved an effective tool to create extended effective fracture length and maximize single-well production in South Sulige tight gas field, with potential cost saving from needing fewer wells to deplete the same reservoir area. This technology, along with the properly designed workflow described in this paper, can also be widely adapted in other tight reservoirs.
Very Rich Laboratory Data Set Paves the Way for Miscible Gas Injection Evaluation Onshore Abu Dhabi
Authors: Larrouilh B. , Mogensen K. , Dehane A.
Published: October 2023

Phase equilibrium calculations require experimental lab data to constrain component properties in an equation of state (EOS) model. In this work, we evaluated the miscibility behavior of four different injection gases for a reservoir onshore Abu Dhabi containing medium-light oil.

The extensive experimental program included swelling and slimtube experiments using CO2 as well as three hydrocarbon gases, in addition to conventional black-oil experiments. Based on the large company PVT database, gas additions in the swelling experiment were carefully designed to reduce uncertainty on the transition point where the swollen fluid type changes from oil to gas. We developed several fully tuned EOS models by gradually lumping down while monitoring the match quality. Due to the richness of the injection gases, C2 (15 mol%), C3 (15 mol%), C4 (10 mol%) and CO2 were kept as separate components resulting in a 10-component final EOS description. The compositional data showed a distinct tail effect above C20, which we believe is a lab artifact. The plus fraction was therefore lumped back from C36 to C20 to characterize the composition from C20 up to C80. This step improved the match of the dead oil properties.

While the swelling data were matched well, the slimtube recovery data yielded some uncertainty on the MMP estimate, especially for the CO2 test. We made use of the reported effluent gas composition to show that one of the points denoted as immiscible in the lab report is most likely miscible. We tested several EOS-based MMP algorithms and found them to give similar MMP estimates for the hydrocarbon gases whereas the CO2 MMP was predicted with a much larger spread. Our view is that for CO2 flooding, cell-based simulations capture the dynamic behavior of miscible displacement better than the key tie-line approach.

The tuned EOS model reproduced the single-phase density very accurately, which is important for the saturation estimation in the transition zone. Several injection gases appear suitable for miscible flooding and further screening studies are now ongoing.
Subsea Debottlenecking Project Increases Production from Caesar Tonga Field, Gulf of Mexico
Authors: Fowler S. , Lammers K. , Ramsey J. , King T. , Coker T. , Ford D.
Published: October 2023

The Caesar Tonga development is a subsea tieback located approximately 112 miles south of Dulac, Louisiana, in the Green Canyon (GC) area of the Gulf of Mexico. It is jointly owned by Anadarko US Offshore LLC (Oxy), with 33.75% working interest (WI), Equinor (46% WI), and Chevron (20.25% WI), and operated by Anadarko Petroleum Corporation (Oxy). The field was discovered in 2006 and achieved initial production in 2012. The Constitution Spar is the host facility (100% Oxy-owned), which was originally installed in 2005 to develop the Constitution and Ticonderoga fields. The Constitution Spar sits on US Outer Continental Shelf block GC 680, which has a water depth of approximately 4,975 ft. The platform's topsides were modified to accommodate the Caesar Tonga subsea development, which lies east of the spar in water depths ranging from 4,650 ft to 5,120 ft (Fig. 1).
Excellent Engineering Solution in Compressor Area to Avoid Project Delay
Authors: AlQaydi Alya , Awadhi Ibrahim Al , Gongade Ashish Shivaji , Locharla Haribabu
Published: October 2023

Green field projects always have an advantage in terms of optimization because everything can be planned with a calculated time barrier. Whereas for brown filed projects, it is a difficult task due to multiple challenges such as limited shutdown time, limited layout space, accessibility for construction, and so on. This paper demonstrates an excellent engineering solution for overcoming these challenges while replacing the existing compressor without requiring major piping/civil modifications.

During a routine asset integrity assessment, it was decided to replace one of ADNOC GAS's existing compressors with a similar one that had the same footprint, nozzle sizes, and orientations. As a result, no significant engineering is required, and only minor adjustments may be required, which can be managed as residual engineering during construction. Consequently, the Purchase Order for the compressor was placed before any engineering activities based on the limited period of the shutdown window.

Since the existing compressor was very old and the design data was unknown, it was difficult to determine the nozzle loads. However, based on the new compressor design data/ nozzle loads, a stress analysis with existing piping configurations is required to ensure the piping system's integrity. It was identified that the new compressor nozzle's allowable loads are much lower as per the latest design code, API 661. The existing piping configuration is imposing more loads than expected due to the need for more flexibility in piping layout configuration. Moreover, the new compressor vendor denied the request to increase the nozzle loads. Consequently, the existing piping routing has to be modified to achieve flexibility in the piping system and meet the nozzle load requirements. With the available shutdown window, there was no time to obtain additional pipe material or change civil supports.

To overcome this situation, enhanced engineering with specialized stress analysis skills and advanced techniques were used to study various options for minimizing the piping/civil modifications as much as possible while meeting the nozzle loads. The best engineering techniques include utilizing the existing support locations, minimizing piping routing/support modifications, and minimizing civil and foundation modifications. By doing so, the compressor was installed without any changes to the vendor's technical requirements and with significant cost savings in implementation while adhering to the available shutdown window.
Green Hydrogen for Oil Industry Green Mobility
Authors: Castagnini Marco , Rinaldi Michele , Pojatar Dejan , Castagnini Massimiliano
Published: October 2023

Green Mobility, intended as ground transportation by zero carbon emissions vehicles, like BEV and FCEV, is growing everywhere in the world. The Oil and Gas Industry, in our opinion, should lead this transition implementing more and more Green Mobility solutions for personnel, cargo and working equipment.

In Kazakhstan, we have a very limited diffusion of Green Mobility and zero in Oil and Gas industry.

Kazakhstan has a very mature Oil and Gas Industry and a coal/oil-based power generation.

Kazakhstan is also proposing as one of the major Green Hydrogen exporters to Europe, with a recent agreement signed with EU and a large part of the territory scarcely populated favorable both for solar and wind harvesting.

Green Spark has decided therefore to install a pilot project to demonstrate for Oil and Gas Operators, Green Mobility.

The contest is challenging for the most popular Green Mobility solutions (BEV and FCEV), therefore we hope with this study and with the implementation of the Pilot Project to provide a concrete opportunity for Oil and Gas Operators to consider the Green Mobility as an easy achievable target to perform their business in a more sustainable environment.

A comparison between performance of BEV and FCEV will be part of our study, covering the concerns may emerge from the climatic of West Kazakhstan with very long and rigid winters.
Integration of a Production Optimization System with Intelligent Well Surveillance for an Effective Reservoir Management in Abu Dhabi Field
Authors: Al Jawhari M. O , Bazuhair A. K , Lopez J. E. , Alqemzi M. , Cremades P.
Published: October 2023

In the world of petroleum engineering, maximizing oil and gas production minimizing operational costs and environmental impact is a constant challenge. To meet these objectives, production optimization systems have emerged as a critical tool in the industry. These sophisticated software solutions leverage advanced data analytics, machine learning, and artificial intelligence to improve the efficiency, safety, and profitability of oil and gas production operations.

During the last decade, ADNOC has leveraged its production growth through implementation of best available technologies and applications, which include data streaming and real time visualization. These, combined with Artificial Intelligence to perform data analytics will provide the tools to develop a Digital Oil Field and unlock opportunities to maximize value.

The strategy of the Oil Companies is aligned with Digital Transformation to get on to the Oil and Gas new trends of optimization, sustainability, and profitability with maximum energy with minimum emissions.

Digital Transformation projects goes beyond automation therefore integrate Big Data, technology, and people to generate value. The implementations should optimize asset management to boost performance and finally under all stages of the projects, one of the focuses is to empower people to make faster and better decisions.

Oil fields with complex-behavior wells or with a big number of wells offer challenges that requires an adequate, opportune, and effective production optimization to reach a sustainable and cost-effective development. A big offshore carbonate field with 43 oil producer wells from different reservoirs distributed in tow islands is one example to address with production optimization tools.

With thousands of measurements acting as model control points, there is a tremendous potential to optimize well performance and have real time updated models for wells and network. Optimization proposals are then provided for further action.

Production Optimization Systems (or Production System Optimization - PSO) are integrated software platforms that enable petroleum engineers and operators to gather, analyze, and visualize data from various sources in real-time. These systems incorporate state-of-the-art algorithms to model reservoir behavior, production rates, and field operations. By analyzing large datasets, they provide actionable insights and suggest strategies to optimize well performance and streamline production processes.

This paper discusses and explore a recent approach of an inhouse developed Production Optimization System used for technical evaluation of well inflow-outflow parameters, sizing of tubulars and accessories and identification of bottlenecks with the key features, and benefits.
Hybrid and Mobile Solar Power for Well Interventions Minicamp in Block 61 Oman
Authors: Al Shidhani T. , Al Juma M. , Al Harrasi S. , Najwani M. A. , Al Shereiqi K. A. , Al Amri K. , Natividad L. , Destremau A.
Published: October 2023

Rig-less well intervention operations, typically including well-works, stimulation and testing (S&T), in bp Block 61 in Oman, normally requires the utilization of diesel-operated engines, such as generators and pumps. This is due to the fact that the nature of these activities call for constant movement from one well site to the other, and hence ease of equipment moveability is paramount to ensure efficient mobilizations. However, the concern with diesel engines is that they generate carbon emissions. As a result, with bp Wells Oman team’s vision to reduce dependency on diesel generators and ultimately reducing emissions, a mobile containerized solar-battery-diesel hybrid power system was implemented.

The rig-less minicamp was identified as one of the main energy consumers in well intervention operations. Conventionally, the minicamp was powered by two diesel generators, one served as primary and the second as back up. Not only did this lead to carbon emissions, but it also created noise pollution for the personnel.

To reduce the dependency on diesel generators in the minicamp, the containerized hybrid power system was introduced. On a single trailer, two containers housed both the solar panels and the battery system. The solar panels were designed in a sense where they could be easily unfolded and folded. This allowed the system to be not only more environmentally friendly, but also remain mobile to be suitable for remote well sites.

The hybrid system was commissioned in December 2021. The cumulative emission savings since then is estimated to be up to 53,500 kg CO2eq. The combination of battery storage and solar panels enabled to completely shut down the diesel generators during daytime hours. Additionally, a great milestone was achieved in November 2022, where the electricity produced from solar, and battery covered 50% of the minicamp energy requirements. In addition to the environmental benefits, the system also provided operational benefits, as the containerized design allowed for easy transport and installation. During 2022, the system was mobilized at least 28 times and commissioned in every new wellsite on average in less than 6 hours. To add to that, the crew welfare was significantly enhanced as the noise produced by diesel generator was eliminated during the day-time hours.

The system was complemented with remote real-time monitoring of its performance. This aided in optimizing its efficiency and identify potential issues. Several lessons learned and improvement opportunities were captured during the implementation of this system.

The purpose of this paper is to detail how the team pushed the operational envelope to introduce this hybrid technology, and share the journey detailing the planning, design, implementation, lessons learned, scalability and improvement opportunities with the target of minimizing carbon emissions in wells operations.
Preparation, Execution, and Associated Challenges for Utilizing the First Successful Closed Loop System Methodology Worldwide in Underbalanced Coiled Tubing Drilling in ADNOC'S Fields
Authors: Osama Mohamed , Sumaida Ali Sulaiman Bin , El Shahat Ayman , Al Mutawa Ahmed , Almazrouei Saeed , Saleh Abdalla , Yousfi Fawad Zain , Almteiri Nama Ali , Baslaib Mohamed , Mantilla Alfonso , Deshmukh Rohit V. , Solaiman Tarek , Abdulsallam Fouad , Ladmia Abdelhak , Rangel Pedro , Rennox John , Cui Shuai , Jumagaliyev Yerlan , Basha Maged
Published: October 2023

Due to the declining reservoir pressures in some of its onshore gas carbonate fields, Operator decided upon an initial 3-wells UBCTD, (Underbalanced Coil Tubing Drilling), a campaign in its onshore fields, The objectives of these operations were to evaluate the applicability of the technology in these fields, to understand requirements and methods of the technology and to evaluate the benefits of drilling the target formations in an underbalanced mode.

During the planning phase, the Operator conducted a feasibility study that flagged potential limitations to deploying UBCTD operations in existing wells, due to limitations on the completion design and other factors. All of this resulted in the plan to drill fit-for-purpose wells to the top of the target reservoir to facilitate the deployment of the technique. These wells were completed with 5.5/4.5 in. Tubing and 7 in. Liner and left with a 100ft open hole interval from where CT drilling operations would later continue. The results ofthe feasibility study nevertheless, additional detailed engineering work was performed in all aspects of the design by the operations team to ensure the success of the trial, including a review and validation of the available data and the feasibility to deliver the stated objectives (lateral length, underbalanced conditions, minimal flaring operations, drilling fluid re-circulation, etc.).

As a result of this approach, all three wells were successfully drilled in underbalanced conditions and to the target lateral length of 4,000 ft. Well, placement was facilitated using Biosteering techniques and continuous monitoring of the well performance vs. drilled footage, allowing steering decisions to be made in real-time to maximize the production of each lateral, resulting in outstanding production results of 3x sustainable production of similar wells drilled conventionally, (after stimulation).

This paper describes the key engineering decisions and assumptions taken during the design process, as well as methods applied during the drilling operation to achieve the best well’s performance. The lessons learned from the project will serve as a launching pad for planning and efficiency gains for future UBCTD operations in the region.