bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital Twin and Big Data Technologies Benefit Oilfield Management
Authors: Lai Wenhua , Zhang Hu , Jiang DaWei , Wang YanHui , Wang RongDe , Zhu Jun , Chen Qiulin , Gao Yuan , Li Weixiang , Xie Dengpan
Published: October 2022

The oil & gas industry has been value added from our digital assets since this new century, which helped our industry dig out more advanced algorithm, more robust logic to address the challenge from HPHT wells and deep-water wells. Nowadays the operators are facing much more challenges in oilfield management especially how to improve their decision efficiency and situation awareness.

Thanks to the different sensors we deployed on oilfield from drilling to completion and production, tremendous data contributed to the digital asset we are having now. The digital twin makes oilfield management much easier than ever before, hundreds of wells’ performance could be displayed in front of the decision maker or key management level of oil companies, and big data technique helps them get easy understanding of real time behavior on well construction progress, cost management, pain spot of each project. Combining these two methods, it is possible to have an up-to-date awareness of oilfield development status and perceptual intuition to very detail situations.

There is a major operator manages over 200 wells per year and some of these wells are challenging exploration well with measured depth over 20000ft which requires experienced team to get the well to total depth, also a lot of shale gas wells with lateral intervals over 8000ft which demands intensive control of cost. All above operations or targets need be done under a safe and efficient way, then the management team taking digital twins to monitor the real time well status which help them get up to date information about whole oilfield status like drilling, completion, production and more. Big data analysis is also used to help enhance the decision- making efficiency and overcome puzzles that traditional method could not solved, like recommending the best practice way on well construction engineering parameters, or ROI (return on investment) assess. The oil company could achieve a better management level with less human resources and much more workload.

By the advantages of digital twins and big data analysis, the oil company now managing more than 200 drilling rigs and 300 completion wells in the high efficiency way, and now involving the production wells into next phase digital construction target. Furthermore, considering develop an integrative digital twin of geology and engineering map which get whole formation and well construction more intuitive. Besides, it is proven that digital method like digital twins and big data technique could improve the skill of oilfield management significantly, which optimized the resource and expenditures investigated in modern oil and gas industry.
Digital Integration to Realize the Limit (RTL) in the Giant Greater Burgan Reservoir
Authors: Dashti Qasem , Abdulrazzaq Hanan , Al-Shammari Nouf , Al-Habashi Haytham , Al-Rumaidhi Meshal , Franco Francy , Muhammad Yaser , Prakash Roshan , Iheanaetu Samuel
Published: October 2022

KOC-SEK asset has the main goal of maintaining, increasing, and optimizing the production of the Greater Burgan, the largest clastic reservoir in the World. Discovered in 1938, Greater Burgan is a multilayer formation with large hydrocarbon volumes of different oil type (from heavy to light) for which a detailed characterization and exploitation strategy was required to develop a sustained asset production.

With the asset facing multiple challenges to maximize recovery and sustain target production field rate, one of these challenges has been to optimize the segregation of a large number of wells into 15 gathering centres. This is to ensure de-bottlenecking and to address back-pressure issues of the production networks while flowing wells in their optimal operational envelope to avoid the rapid depletion of the reservoir and the increasing water production.

Due to the vast number of wells, the intricate network, the limitations in the gathering system and the dynamic operations, maintaining and sustaining the reservoir performance requires continuous surveillance, rapid and robust understanding of the different variables at reservoir, well and network level to make timely decisions and maximize reservoir recovery. To support this, a standardized and integrated system based on data analytics and numerical models, has been developed in the context of Realize the Limit (RTL) of the Greater Burgan reservoir as a tool for the quick identification of potential oil gain opportunities, the evaluation of bottlenecks across all the production system, and track and measure the impact of different proposed operational and development scenarios to unlock potential production and support optimum production forecasting.

The system has been developed in a digital framework, with inputs from a multi-disciplinary team to define the datasets, calculated parameters and visualization requirements related to reservoir properties, well completion status, operational parameters, and key indicators from subsurface and surface hydraulic models. These has been integrated to identify key performance issues involving several aspects of the reservoir's development and operational plans. Also, the process provides a high-level overview and a platform for all asset groups including management, field development and operations, where observing the same set of results can initiate collective decisions that improve wells, network and facility management and enhancement recommendations.
Enhancing Drilling and Production Through a Digital Twin Methodology
Authors: Thomas Philip Titto , Ziatdinov Sergey
Published: October 2022

In recent years digitalization has become one of the fastest growing disciplines in the oil and gas industry. Digital solutions reduce project costs, improve personnel and process safety. However, underestimation of the deployment complexity can also bring severe damage to the project execution, unnecessary delays, and ramp-up costs. To minimize negative effects and smoothen delivery process digital twins provide for oil and gas the opportunity to create a digital representation of the equipment, processes, and people behavior.

Drilling is a very capital-intensive part of the oil and gas industry. It usessophisticated heavy machineries and typical rig contains various equipment from different vendors.Moreover, drilling process by itself has a lot of uncertainties and depends on human behaviors. Thismix makes most service and operating companies very cautious in introducing new technologies.Therefore, any solutions that can smoothen delivery process and minimize or even avoid any hitchesduring deployment bring a lot of benefits to the industry. Digital twin methodology is an ideal way toaccelerate new technologies deployment through offline full-scale digital testing.

The paper highlights efforts to assist operators and drillingcontractors to create a methodology to optimize usage of their assets and improve their processes, using a combination of Systems Architype model and Systems Development lifecycle (SDLC), both well-established methodologies for systems development. Thefocus is on performance improvement, non-productive time reduction, oil and gas productionmaximization. Through emulating rig equipment, drilling process and personnel behavior it is possible toidentify the most critical parameters which guarantee reaching technical limits. Application of digital twin isan iterative process and typically includes several steps. Starting with setting targets, like negative impactreduction of the drilling process on subsequent production. Following by determination of the optimaldrilling parameters based on either historical or modelled data both from drilling and production. Theseparameters are the basis for the new drilling methodology. All deviations from existing drillingmethodologies and generic programs must be carefully analyzed and implemented. Finally drillingmethodology built using digital twin is ready for implementation in real world. The received data is goingto the next iteration to improve the methodology. This approach allows us to train personnel for field specificsituations without risking expensive mistakes in the real world.
Real-Time Enabled Digital Technologies Solution to Deliver Consistent Performance in Gas Wells Construction
Authors: Barrera Edison , Nunez Andres , Corona Mauricio , Dorantes Arnott , Atriby Kamal , Aswal Uttam , Ponomareva Daria
Published: October 2022

The oil and gas industry has constantly evolved riven by data management and technology application. Although the first well was drilled over 150 years ago, the last decade has shown a huge step change leaning towards digital technologies and automation dependency. The main purpose is to leverage from field experience in multiple disciplines, enable quick data transmission for accurate decision making and automate repetitive processes, aiming to reduce lost time, increase performance and ensure consistency.

A multi-rig integrated project of gas wells construction in a field in the Middle East has successfully introduced selected Real-Time digital technologies connected with rig automation features and, along with standard practices developed through years of experience, has proven consistency assurance delivered by the implemented solution. Fully automated technologies combined with high-frequency Real-Time data generators and the latest generation of algorithms that model downhole conditions precisely, further enhance drilling performance, and allow faster and more reliable detection of non-desirable downhole events.

This paper describes the strategy to combine fit-for-purpose technologies which deliver digital inputs working in communication with advanced digital technologies to deliver a solution for multiple stages of well construction operations to increase performance, reduce major risks, ensure procedural adherence and well delivery consistency.
Gap to Potential Identification through An Online Process Digital Twin
Authors: Kumar Suresh Machingalthodi , Al Mahmoud Mahmoud Abdul Hameed , Al Yahyaee Nawal
Published: October 2022

An application has been deployed to identify the gap to potential and provide actionable intelligence to the plant operators on a real time hourly basis to maximize the value-added products and minimize energy consumption in a natural gas processing plant. An online digital twin based on thermodynamic models coordinating the underlying multisite Advanced Process Control (APC) applications, has been implemented enabling multisite gap to potential identification.

Model Predictive Control has been for decades the de facto technology adopted in the oil and gas sector to optimize the process operations and improve yield. This falls short of identifying the unconstrained regions of optimization. A fit for purpose online thermodynamic model was developed for the entire NGL value chain. This is then mapped with the underlying APC limits as bounds. A data reconciliation algorithm coupled with a stead state detection algorithm creates first the exact replica or digital twin of the process plant. An optimization algorithm then identifies the true gap to potential and provides the advisory targets.

The application solution is scheduled to run every hour mapping the real constraints of the plant in real time. This ensures that the optimized targets provided are realistic in nature and is within the safe operating limits of the plant. The online digital twin resulted in the following:

➢ A true representation of the plant with the mass and energy "balanced" across the plants on an hourly basis representing the true operation of the plant. This has resulted in the identification of suspected process measurements across the plant. ➢ This digital twin has enabled monitoring of the true representation of the different efficiency parameters like the polytropic efficiency of compressors, heat exchanger fouling etc., which can further be used as an input to Machine learning algorithms for the calculation of remaining useful life. ➢ Dynamic calculation of the energy consumption and setting up of the dynamic baseline as against static baseline for energy KPIs ➢ The optimization algorithm further provides advisory for identifying the optimized targets, which on implementation will enhance the yield with reduced specific energy consumption. ➢ Identification of the hardware constraints of the plant with estimated dollar value impact for unit change in that constraint enabling debottlenecking studies.

This is a first of its kind implementation, in a geographically separated multisite operations. In an online environment, this digital twin can provide the optimized advisory targets, resulting in increased revenue and an attractive ROI. In an offline environment the same solution can be used for what if analysis and debottlenecking studies. Buoyed with the success of this project, there is a plan to scale up, integrating the upstream and downstream operation.
Monitoring and Troubleshooting of Subsea MPFM by KPIs and Virtual Metering Application in Offshore Environment
Authors: Ursini Fabrizio , Torsello Antonio , Fiorita Simone , Akinmade Abimbola , Ciriello Giuseppe , Vignati Emanuele , Tumiran Tumiran
Published: October 2022

This paper presents the application of real time monitoring techniques on production allocation in a complex scenario, focusing on definition of dedicated KPIs to identify possible issues in flowmeters installed at well level. The analysis includes a comparison with a dedicated Virtual Meter system.

Real time production allocation is monitored by means of a dedicated KPI dashboard, detecting any possible drift in Multiphase Flowmeter (MPFM) measurement processes. The ratio between reference measurements and MPFM readings is calculated for assessing allocation quality. Furthermore, an independent virtual flowmeter (VM) technique was developed to estimate well production rates and compare them with the MPFM flow rates. The VM relies on analytical models (Vertical Lift Performance) to correlate real time pressure losses in the tubing with flow rates. KPIs monitoring and VM are developed in a digital environment available to the engineers operating the field to provide a quick problem detection and a promptly response.

During the initial production phase, a good match between subsea and topside total MPFM readings and daily production figures resulted in a robust production back allocation. This trend was confirmed by the dashboard of allocation KPIs being within the acceptable thresholds. The Virtual Metering system was calibrated against MPFM rates during this initial production phase. After one year of production, KPIs showed a drift between the total subsea and topside MPFM readings, while a good match was achieved by virtual metering, topside MPFM and daily fiscal production. A well by well comparison between VM and MPFM installed at wellhead allowed to identify reliable MFPM and pinpoint the ones requiring retuning. In the meantime, during the troubleshooting process and actions implementation to restore the MPFM functionalities, the virtual metering estimations were used in the production back allocation process.

A combined application of the Virtual Meter and the KPIs monitoring enabled us to improve the quality of back allocation relying on the best type of well production estimation available at each phase of production. The methodology described in this paper entered the daily routines followed by engineers operating the field.

This paper shows the benefits of the digital platform for asset monitoring, as well as the technology that allowed to set up a cooperative environment. Sharing real-time data and model based estimation for a multi-disciplinary team, from Reservoir to Operations, facilitated working together to achieve faster trouble shooting and optimize production performance.
Improving Facility Maintenance through Inspection with the Latest Ultrasonic Imaging Technology
Authors: Pörtzgen Niels
Published: October 2022

For a safe, reliable and efficient operation of facilities, knowledge and information of the condition and integrity of the assets are essential. Therefore, assets must be inspected on a regular base, preferably with non-destructive methods. Many of such methods are known in the industry (e.g. radiographic, magnetic, ultrasonic testing etc.), however their application is often restricted and the resulting data from the inspection is not adequate and/or sufficient for the asset integrity management.

Due to advances in ultrasonic hardware and sensor technology, a novel approach for non-destructive testing based on ultrasonic imaging, IWEX, has been introduced. With this approach, an ultrasonic ‘fingerprint’ called a Full Matrix Capture (FMC) data set, can be measured. With the FMC data set representative 2D and 3D images from the interior of metal components (e.g. welds) can be re-constructed. For the inspection of such components, real time scans can be made in order to reveal possible flaws.

The IWEX technology has already successfully been applied for the inspection of girth welds in newly constructed pipelines ([1], [2]). Furthermore, the method has recently been recognized by international codes and standards (ISO [3], ASME [4]), which opens the door for both new construction and in-service inspection applications in industrial facilities. In this paper, we will present the principles of ultrasonic imaging with the IWEX method. An example will be presented of an actual use case, concerning the inspection of welds in stainless steel pipes in an industrial facility. The welds contained cracks which were in some cases detectable with radiography, but height sizing was not possible. With the IWEX method, the cracks could reliably be detected, and it was possible to determine the crack heights. The height sizing accuracy was confirmed with known artificial targets in a representative reference block. Based on the accurate sizing results, it was possible to perform a fitness for service analysis which allowed a safe continuation of production in the facility.

The use case of the IWEX method illustrates how this new technology facilitates improved maintenance strategies for the industry by enabling the possibility to obtain sufficient and accurate information during inspection. As a next steppingstone the 2D and 3D images can be stored digitally such that they can be used to monitor and predict the condition of the asset over time using novel analyses concepts such as pattern recognition by neural networks.
Monitoring Mechanical Equipment on an Offshore Rig with Contrastive Learning on Acoustic Features
Authors: Kumar Ankit , Priyadarshan Amit , Sekar Pragadeesh K
Published: October 2022

Mechanical equipment, operating in the oil and gas industry produces a wide range of sounds, often culminating in noise. A functional equipment creates a standard sound, while malfunctioning equipment creates an anomalous sound. In this paper, we propose an application of a contrastive learning algorithm to detect anomalous sound amidst industrial noise, which in turn helps in the identification of the malfunctioning equipment on an offshore rig.

The recent success of contrastive learning algorithms to detect novelty in visual representation has inspired our work. We hypothesise that for most of its lifetime, equipment operates normally. Instances of malfunction that produce anomalous sound and hazardous consequences are rare in their defined lifetime. To this end, we implement a contrastive learning algorithm to identify similarities between audio clips using 10-second length normal-audio clips collected from 6 different equipment for training purposes. It extracts local and global features from the augmented audio clips and presents them in latent space, where the loss function differentiates between normal and anomalous sound. Finally, we input normal audio and anomalous audio into the algorithm.

The performance of the proposed algorithm is measured using Receiver-Operating-Curve - Area-Under-Curve (ROC-AUC) (Koizumi et al., 2020; Nunes, 2021)[5]. It successfully differentiates normal and anomalous audio to achieve an average ROC-AUC of 0.77 on the scale (0-1). 26092 audio clips of normal equipment sound and 6065 audio clips of anomalous sound from Valve, pump, fan, slide-rail etc., are used to perform the proposed experiment. Diverse industrial anomalies produced by unbalanced-voltage change, clogging, leaking, contamination, loose belt, no grease etc., are present in the dataset. The proposed methodology of contrastive learning consists of a data-augmentation module followed by an encoder and a Neural Network (NN). Data augmentation transforms the input audio clip to ensure robust performance. The encoder extracts the features from audio clips and projects them in the space of contrastive loss function with the help of NN. Automatic failure detection using Artificial Intelligence is essential for Industry 4.0. Prompt decision by monitoring sound produced by mechanical equipment holds immense potential for asset maintenance in the petroleum industry.

This paper is one of the first instances wherein the application of contrastive learning for the maintenance of mechanical equipment has been demonstrated. The proposed method is a unique approach towards anomaly detection using acoustic-features and it significantly reduces human intervention in hazardous and hard-to-reach environments.
Field Study Application of Ensemble Based Assisted History Matching and Optimization for Reservoir Management
Authors: Forouzanfar Fahim , Verma Santosh
Published: October 2022

Design of an optimal reservoir management strategy requires reliable reservoir performance prediction by the simulation models as well as implementation of robust and efficient mathematical optimization techniques to optimize the operating production and injection well controls. This paper describes an overall reservoir management workflow which consists of (1) the application of a novel data assimilation method for assisted history matching, and (2) the optimization of water-alternating-gas (WAG) injection cycles to maximize the life-cycle estimated ultimate oil recovery (EUR) of the reservoir.

In this field study, the permeability field of the reservoir model is tuned to match the historical data. An iterative ensemble smoother (iES) optimization algorithm is used for the tuning, with a parameterization method based on coarsening of the property fields. The observed data includes the production and injection streams, the well bottom-hole pressures and static pressure measurements. The proposed parameterization combined with the iES algorithm resulted in a near-perfect match of the historical data. The property field tuning was within the acceptable and prior uncertainty ranges.

For the WAG injection optimization study, the field management strategy and the list of WAG wells were given and fixed. The strategy included target average reservoir pressure, voidage replacement ratio and fluid material balance, in addition to the individual well limits and targets. The study parameters were water and gas injection cycle length. A design of experiment was done to understand the range of EUR for the field and understand its sensitivity to the optimization parameters. Next, a stochastic optimization algorithm was utilized to optimize the life-cycle EUR of the field by adjusting the injection cycle's length. The optimization was successful in improving the EUR of the field - the optimized ultimate recovery outperformed the best engineering design case and the ensemble of Latin Hypercube design cases. That said, the underlying field management strategy seemed to moderate the input controls, hence, the ranges of EUR improvements were relatively small.

This study presents a successful application of novel ensemble based algorithms for field management and optimization, where the workflows outperformed the manual solutions both in terms of quality as well as the amount of effort required to do the study. The presented ensemble methods were efficient for estimating the sensitivities required for optimization of large scale problems - a critical aspect for field applications with large and computationally expensive simulation models.
Solving the Problem of Sulphur Deposit in Gas Injection Compressors
Authors: Yadav Sudhanshu Kumar , Al Muhairi Mohammad Ahmad , Al Khanbouli Mohamed Saeed
Published: October 2022

Paper debunks the theory of JT effect being responsible for Sulphur deposits and provides explanation on source of the problem of elemental Sulphur in dry gas seals of Gas Injection Compressors. The paper provides a practical and economical way forward to solve the problem of Sulphur deposit. This solves the problem of frequent failure of dry gas seals in Gas Injection Compressors. It also simplifies the Dry Gas Seal conditioning system design and improves Dry Gas Seal performance and reliability at compressor starts and stop (including ESD and CSD).
Digital Wellhead Integrated System for Production Management
Authors: Avila Reyes Ricardo , Machado Miguel , Torre Mario , Sharma Jitender , Gey Gian Marcio , Koa Johnson , Edwards Thomas
Published: October 2022

The oil and gas industry is lagging behind many industries in the adoption of technology and digital transformation. Our industry must transform at speed and scale to reap the available benefits of such technologies. Managing well integrity through personnel physical presence at the wellsite to take recordings increases the time to react to issues, the time to collect data, and the time to implement actions, and the high field trip rates introduce an increased risk to employees.

A digital wellhead integrated system (DWIS) provides information on wellhead parameters from smart instrumentation and achieves operational intelligence via edge computing. This solution improves the response time between production data and field actions to optimize and improve operational performance following workflow parameters. DWIS provides real-time monitoring, data collection, and management of well conditions, which minimizes the effects of human interactions, while providing consistent information that can be used for future health maintenance activities thus mitigating the risk of unexpected events. Cost efficient remote monitoring and control of well activities prolongs the life of the well and promotes savings.

The DWIS has been deployed and successfully tested in North America, South America, and the Middle East. A single DWIS implemented with a client resulted in production gains of 400,000 bbl./yr. and reduced 10,000 miles of driving—reducing the carbon footprint in a harsh environment. By providing human intelligence at the wellsite through edge computing and smart instrumentation, data can be generated, and actions taken to reduce expensive unplanned maintenance, offline outages, resource-intensive costs, and carbon footprint. Furthermore, this infrastructure at the wellsite enables ideas for new workflow implementation such as site monitoring via computer vision and more elaborate production and optimization workflows, creating a truly intelligent asset. DWIS maintain well integrity and provide continuous monitoring to optimize oil and gas production.

This DWIS supports well integrity maintenance strategies providing real-time control and well optimization enabled by smart instrumentation, surveillance systems, and intelligent workflows powered by artificial intelligence/machine learning algorithms executed at the edge and, in some instances, at the cloud level.
Achieving Productivity and Operational Efficiency, and High-Quality Data Through Automation in Well Log Data Quality Control and Acceptance Process Using AI/ML Techniques
Authors: Akbar Bibi Hussain , Al-Aradi Huda Jassim , Achmad Pajar Rachman , Khan Waqar Ullah
Published: October 2022

Well log data and reports volume generated by oilfield operations in Kuwait Oil Company (KOC) have increased tremendously over the last decade. Currently, KOC receives around 100 to 200 well log packages every week. Each package may contain hundreds of well log files. Mostly, the processes to receive, manage and load this amount of data into the Corporate Database were manual, involving 7 to 9 resources. Logging companies may have to wait a minimum of a week to receive the decision if their data delivery is approved or rejected. The Exploration and Production Information Management (E&P IM) team started an initiative to accelerate and automate these processes by developing and implementing a solution using Artificial Intelligence and Machine Learning techniques to increase productivity and operational efficiency and achieve high-quality data. The main results are high-quality data that meet E&P IM Well Log Standard and Specification, the processing time is reduced by 80%, and the operational efficiency is improved by 66%, allowing the resources assignment to more valuable activities.
Orifice Meter Condition Based Monitoring-Tracing the Ten Technical Developments to Standards Board Acceptance
Authors: Steven Richard Neil , MacGillivray Alick
Published: October 2022

Orifice meters can have advanced diagnostic capabilities which facilitate Condition Base Monitoring (CBM). These diagnostic methods have developed over time and have now reached the maturity to be included in the latest API, AGA, ASME, and ISO standards. This paper describes their development.
An Innovative Method of Water Management by Desalinating the Produced Water Using Thermal Renewable Energy
Authors: Al Ruheili Sharifa Mohammed , Tiefenbacher Felix , Al Mahrami Khansaa Hamed , Shahin Nazir Othman , Al Jaaidi Omar Salim
Published: October 2022

Produced water, which in many cases shows a high degree of salinity, is currently managed using water disposal wells and evaporation ponds. Both methods are conventional and have negative environmental impacts. ARA is adopting a unique and innovative method to manage high salinity produced water in an environmentally sustainable way by extracting potable water from produced water and reducing discharge water volume by at least 50%. For desalination of the produced water an innovative combination of forward and direct osmosis technology is used. This process is driven mostly by thermal energy which is provided to 100% solar thermal collectors.

The structure of the plant is as follows: A solar thermal power plant consisting of 2 desert- and oilfield-proof solar thermal collectors ("HELIOtubes") with thermal energy storage (TES) using pressurized water for nighttime operations (24/7). The solar thermal plant powers an advanced forward osmosis desalination (FO) and brine concentration Direct Osmosis (DO) unit with pre-treatment unit to cope with the challenging produced water.

This project is in the pipeline for implementation. The engineering and the planning design were successfully completed. Two main results are expected from this project, which is: (i) low-cost and low-maintenance thermal power and (ii) desalinated water from the produced water meeting the regulatory specifications.

It is a state-of-the-art system integration engineering based on the simulation of the innovative desert-proof solar thermal plant including TES using 10-year historical satellite-based irradiation data to show optimal use of renewable energy. Lab studies show how low energy consumption pre-treatment of the challenging produced water with its difficult chemical composition can be achieved, allowing membrane-based forward osmosis to be applied even at a salinity level that is 3-times higher than seawater. That leads to high energy efficiency for desalination also at nighttime based on thermal power from cost-effective TES instead of expensive batteries. This system could be considered a game-changer in the oil and gas industry because it introduces a new water management methodology.
Online Robotic Inspection of Above Ground Storage Tanks without Outage
Authors: Al Shamsi Ali Humaid , Castelino Shan Mohan
Published: October 2022

Above Storage tanks are one of the critical equipment's in the Oil & Gas facility that handle large volume of fluids. Integrity Management of Above ground storage tanks is of utmost importance in oil and gas facilities such as Processing plants and Storage terminals. Periodic Internal inspection is a key element on Above ground storage tank Integrity management strategies. Oil and Gas operating companies are faced with applicable regulations and competing economics of expensive and potentially dangerous inspections. To minimize the amount and cost of inspections needed there is need for a technology that performs inspection and assure Integrity while the tank is Inservice and keeping costs, downtime, safety risks, and environmental impacts to a minimum.

Robotic inspection of Above ground storage Tanks can be deployed to conduct detailed investigation and assess integrity of tank while it is in online which is in compliance with Internationally recognized industry codes and standards. Tank internal Online inspection by utilizing the Robotic technique, eliminates high cost of tank downtime, need for temporary product storage, avoid cleaning and handling of sludge, increase personnel safety by avoiding confined space entry
API Pipeline SMS Assessment Program: Key Changes and Learnings from Initial Assessment Outputs
Authors: Frazier Colin M. , Toth S. David , Burr Alexa S.
Published: October 2022

The American Petroleum Institute (API) represents all segments of the natural gas and oil industry, aiming to accelerate safety and environmental progress across operations while meeting global demand for affordable, reliable, and cleaner energy. Through API and partnership with the U.S. Pipeline and Hazardous Materials Safety Administration (PHMSA), state pipeline regulators, and other interested stakeholders, pipeline operators developed API Recommended Practice (RP) 1173: Pipeline Safety Management Systems. API RP 1173 is designed to help operators create a management system structure to systematically manage pipeline safety and continuously measure progress to improve overall pipeline safety performance. The core principle of API RP 1173 is the "Plan-Do-Check-Act" cycle, and it requires an operator to periodically review their pipeline safety management system (PSMS) to the requirements of RP 1173 on a triennial cycle.

In collaboration with industry partners, API developed the not-for-profit Pipeline SMS Assessment Program in 2019 and fully launched the offering in January 2020. In the three years since its inception, API has facilitated 14 assessments of pipeline operators’ safety management systems against the requirements of RP 1173. In doing these 14 assessments, the process for completing assessments has been tested by operators of vastly different sizes, carrying a wide array of products, from very small steam utility operators to large liquids operators with operating regions across North America.

The industry has also identified specific trends relevant to API RP 1173 implementation in conducting these assessments. Specifically, it has created awareness around some areas pipeline operators continue to struggle with in creating a holistic PSMS: 1) ensuring that field-level personnel understands how their roles relate to safety performance relative to the company's PSMS; 2) incorporating learnings from external events into their PSMS so that similar incidents do not occur; 3) incorporating relevant and standardized PSMS requirements into agreements with service companies, and; 4) delineating what RP 1173 requirements mandate programmatic governance or policy within their PSMS (an industry learning).

In this manuscript, API will provide an overview of the PSMS Assessment Program and changes made since its inception, an examination of the key learnings from assessment outputs to date, and a description of how the program is providing a feedback mechanism to improve industry initiatives to help operators implement RP 1173.
Tackling Mixed Scales Issue in Oilfield Using a Novel Robust Scale Dissolver
Authors: Ramly Nora Aida , Hendraningrat Luky , Riyanto Latief Riyanto , Rodzali M Azmeer , Baharuddin Salina
Published: October 2022

The scale problem is turning into a fluid-related flow assurance concern in oil and gas wells at various locations in the Malaysian basin. Flow assurance issues can have a severe influence on the total fluid production trip from subsurface to surface. Oilfield scale comes in different varieties, including organic, inorganic, gas, soap, and mixed scales. In the past, there was only one type of scale dissolver chemical that could be used, making it less efficient to dissolve multiple types of scales at once. The evaluation of a recently developed, so-called robust solid dissolver (RSD), from the lab to a pilot deployment, is presented in this work.

The RSD technology was developed based on a stable micro-emulsion solution that comprises acid and solvent components. Near the wellbore and along the tubing string of an oil well, it can concurrently dissolve organic and inorganic scales. After extensive visual analysis and laboratory experimentation, it was determined that the mixed scales issue was the cause of the oil production's rapid decline. This conclusion was supported by laboratory analysis and observations made from the wellsite throughout the tubing string and near wellbore casing.

Based on laboratory tests, RSD can dissolve mixed scales 100% in 24 hours at well temperature and no incompatibility issue with production chemicals and all the pumping/wireline components. The RSD was developed based on the total organic system that can prevent corrosion, is compatible with hydrocarbon. The RSD was piloted at oil well "1" at Field PN and executed successfully to remove mixed scales and the well was revived. Based on result from the first Pilot, it revived oil well, increased production at a certain level.

By increasing oil production rate and having value creation as a single chemical treatment to address mixed scales concerns, the new RSD has unlocked its potential to revive the well due to mixed scale issues.
Reviving a Complicated Idle Well: A Multi-Intervention Example from the Sultanate of Oman
Authors: Al Gheilani Hamdan , Al Sawwafi Khalid , Cruceru Dragos , Bezboruah Pearl , Charushin Anton , Al Maskari Said , Al Balushi Saja , Makawi Sami , Al Hatmi Hatem , Eltorabi Yousif
Published: October 2022

A well targeting deep a gas formation in the central part of the Sultanate of Oman was drilled in February 2010. At a later stage a fracturing operation was conducted but an integrity issue. This integrity issue consisted of a communication between tubing and casing annulus which led to the well having been isolated with cement plugs. This paper describes a successful work cycle of restoring well accessibility and reviving production from an idle complex well using different means of well intervention.

A Hydraulic Workover Unit attended the well to fix the integrity issue of the casing/ tubing annulus communication. An old casing was recovered and a new one installed. Next a coiled tubing unit attended the well; it encountered complicated well conditions characterized by the presence of metal junk left behind after a previous milling operation. In addition there were 3 cement plugs and 700 m of proppant which needed to be removed in order to establish access to the producing formation. We adopted an ""agile" approach and deployed a "super magnet" by slickline. Following the removal of the cement plugs we cleaned the well from proppant using coiled tubing with sand return management at surface.

The well which was originally planned to be abandoned due to the complexity of its integrity issues was successfully recovered. The integrity issue was fixed by installation of a new external casing patch using a hydraulic workover unit. The approach of using a combination of different well intervention methods enabled reviving the idle well and unlocking access to hydrocarbon reserves. Full passage to the target depth was confirmed which made the operation a full success. Challenges such as the presence of metal junk, logistics constraints to supply a large volume of water for long-interval milling and cleanout operations, management of abrasive sandy returns at surface were overcome through a collaborative approach between all parties involved.

This paper presents a case where we successfully brough back on production a well which had been shut in due to complex well integrity issues. We present the lessons learnt as many of these can be applied to other challenging projects. This show case reveals how the combination of different types of well intervention techniques can help restore production from a well with complex well integrity issues.
Integrated Absorption and Regeneration Membrane Contactor Technology for Removal of CO2 and H2S from Natural Gas
Authors: Mohd Tamidi Athirah , M Saleh Syafiqa , Quek Ven Chian , Hanafiah Mahmat Rashid
Published: October 2022

Regeneration of rich amine using membrane contactor (MBC) is studied with observation on factors of operating temperature, flowrate and pressure. The desorption of CO2 and H2S were analyzed, and as a result operating pressure and liquid temperature were identified as the most significant parameters affecting desorption. Higher acid gas flux was observed at higher temperature and higher flowrate. Desorption of CO2 at higher flowrate is limited by the membrane contact area; whilst H2S was more readily desorbed. The higher operating transmembrane pressure of 0.3 barg is preferred as it provided good control during regeneration operation. The optimized parameter for rich amine regeneration was determined through ANOVA analysis using DesignExpert software. The optimum condition was found to be at 90 °C and 0.3 barg; these parameters were then used for the integrated operation of the absorption and regeneration membrane contactor. Continuous integrated testing was carried out and successfully met the specification for both sections. The absorption membrane contactor was able to remove CO2 from 25% down to 6.5% and H2S from 500ppm to below 20ppm. The regeneration section maintained good desorption of H2S where the recycled amine had less than 200ppm and for CO2 desorption 0.2 mol CO2/mol amine loading was removed.
Super Wells: Disruptive Proposal for Well Production Beyond the Established Fixed Limits (Erosional / Corrosive Limits) Case Study in High Potential Wells in Abu Dhabi Field.
Authors: Almarzooqi Laila Sayed , Alqemzi Meera , Cremades Pablo , Lopez Juan Enrique , Palacios Carlos
Published: October 2022

Early in oil field development, it is possible to discover high-potential wells that allow "thinking outside the box." However, in adverse scenarios (presence of H2S and appearance of asphaltenes), the limits appear to be very conservative. Two of these untouchable limits are the erosive and corrosive limits of fluid velocity. In particular, the use of API 14E RP based models is very conservative because it must be used safely in a wide range of applications in producing and injection wells around the world. Even commercial Nodal Analysis ® suites for their default erosion calculations take the dimensionless C factor = 100 as a reference. The objective of this work is to show a case study in which it is determined the feasibility and theoretical limits of increase production mean model the detrimental effect of erosion and corrosion to take advantage the potential of oil-producing wells with a high productivity index (higher than 8 bpd/psi) to safely optimize your production (greater than 5,000 bpd) with low risk of erosion or corrosion over a 5-year horizon under specific conditions.

Alternative models were based on conservative values of 15 ft/s as the upper erosive limit (Zheng et al. at 2000) and 5 mpy (NACE SP0775) as the upper corrosive limit. Iterations of factor C were carried out up to 125 that allowed increasing the production rate of high potential wells above 5000 bpd. This study allowed to determine a list of candidate wells for a second analysis. This second study was more detailed and was based on an extended model (erosion/corrosion) developed by the University of Tulsa and confirmed that these wells could produce more than 5000 bpd over a period of up to 10 years with very low risk of failure due to erosion or corrosion failures.

From 40 wells of the field evaluated, it was found that of the 12 wells with high potential, 9 wells were found to be viable to produce up to 6000 bpd during the first stage (C factor up to 125). In the second stage of the process the study concluded that it was feasible to increase the production of the 9 wells even up to 7000 bpd without causing significant risks of erosion or corrosion if the water cut was kept below 10%. Field short test was carried out in three (3) wells with satisfactory results.

The application, for limited periods of time, of alternative models that allow the optimization of production of wells with high potential during the early development of large oil fields is possible. If the water cut, and solids production values remain low (water cut less than 10% and solids production less than 0.1 kg/1000 bpd and particle size between 20-50 microns).
Digitalization and Data Automation: The Path for a More Efficient Well Integrity Data Management and Cost-Effective Responses
Authors: NIZAR Mouna
Published: October 2022

Bridging data management gap by gathering all well integrity data in one unique data base. The aim of ADNOC Offshore in-house Well Integrity Data Management System (WIDMS) is to comply with the 3A rule: Accessibility of the data, Accuracy by performing regular quality check and Analysis. The analysis allows to maintain wells barriers robust, to ensure personnel safety and to quickly identify integrity issues to make qualified decisions about appropriate mitigations measures and avoid risk escalation. WIDMS has been developed in-house with inputs and collaboration of various stake holders. An enhancement list has been established selecting the most relevant features that will be added value to the system. Therefore, Automation for sub processes like thresholds calculations and Risk Assessment which gives input for Well Passports that contains all the required information to evaluate the well risks and implement the required mitigation measures.

End users are following a RACI Chart to keep WIDMS database on track and to ensure no data falls through the cracks as all the data workflow is defined through the different steps such as providing data, entering it in the system, informing relevant stakeholders and providing technical clarifications if needed. The result of data acquisition in WIDMS is that data flows across the entire organization, with defined access rights in line with ADNOC Offshore policies. This data is collected from various sources, is a robust data base, essential for evaluating and maintaining well integrity.

It is enhancing well barriers system management by allowing to have full overview of well's barriers performance. Moreover, it allows to have reliable and continuously available data such as annulus pressure data that is critical for well integrity assurance, to avoid the uncontrolled release of hydrocarbons to the atmosphere. Notifications have been implemented so alerts can be sent for engineers to inform about any abnormality and non-compliance. As technology evolves, using paper-based processes, excel spreadsheets, time-based equipment inspection and testing become less effective. Well diagnostics are expensive so utilizing well data analytics through this digital hub project will ease having detailed real time data and quick analysis for early detection of failures and anticipation and reduction of risk escalation.