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Methane (CH4), the primary constituent of natural gas and is the second-most abundant greenhouse gas after carbon dioxide (CO2), accounts for 16% of global emissions. The lifetime of methane in the atmosphere is much shorter than CO2, but CH4 is more efficient at trapping radiation than CO2. Pound for pound, the comparative effect of CH4 is more than 25 times greater than CO2 over a 100-year period. Natural-gas emissions from oil and gas facilities such as well sites, refineries, and compressor stations can have significant safety, economic, and regulatory effects. Continuous emission detection systems enable rapid identification and response to unintended emission events.
The Abu Dhabi National Oil Company (ADNOC) announced that it has completed the first phase of its large-scale multiyear predictive maintenance project, which aims to maximize asset efficiency and integrity across its upstream and downstream operations. ADNOC says its predictive maintenance platform uses artificial intelligence (AI) technologies such as machine learning and digital twins, ADNOC’s to help predict equipment stoppages, reduce unplanned equipment maintenance and downtime, and increase reliability and safety. The company said it expects use of the platform to result in maintenance savings of up to 20%. The predictive maintenance project, which was announced in November 2019, is being implemented over four phases. ADNOC’s predictive maintenance project is part of the company’s digital acceleration program, which focuses on embedding advanced digital technologies across the company’s operations.
We showcase an innovative campaigning and business-focused approach to reservoir monitoring of multiple fields using 4D (time-lapse) seismic. Benefits obtained in terms of cost, speed and the quality of insights gained are discussed, in comparison with a piecemeal approach. Challenges and lessons learned are described, with a view to this approach becoming more widely adopted and allowing 4D monitoring to be extended to smaller or more marginal fields.
An offshore seismic acquisition campaign was planned and successfully executed for a sequence of four 4D monitor surveys for fields located within 250 km of each other on the greater Northwest Shelf of Australia. The four monitors were acquired in H1 2020 comprising (in this order): Pluto Gas Field M2 (second monitor), Brunello Gas Field M1 (first monitor), Laverda Oil Field M1 and Cimatti Oil Field M1.
Cost savings expected from campaigning were realised, despite three cyclones during operations, with success largely attributed to detailed pre-survey planning. Also important were the choice of vessel and planning for operational flexibility. The baseline surveys were diverse and required careful planning to achieve repeatability between vintages over each field, and to optimise the acquisition sequence – minimising time required to reconfigure the streamer spreads between surveys. The Cimatti baseline survey was acquired using a dual-vessel operation; modelling, combined with now-standard steerable streamers, showed a single-vessel monitor survey was feasible. These optimisations provided cost savings incremental to the principal economy of sharing vessel mobilisation costs across the whole campaign.
Both processing and evaluation (ongoing at the time of writing) are essentially separate per field, but follow a consistent approach. Processing is carried out by more than one contractor to debottleneck this phase, with products, including intermediate quality control (QC) volumes, delivered as pre-stack depth migrations. While full evaluation of the monitor surveys to static and dynamic reservoir model updates will continue beyond 2020, key initial reservoir insights are expected to emerge within days of processing completion, with some even earlier from QC volumes. Furthermore, concurrent 4D evaluations are expected to result in fruitful exchanges of ideas and technologies between fields.
The Abu Dhabi National Oil Company (ADNOC) completed the first phase of its large-scale multiyear predictive maintenance project to improve asset efficiency and integrity across its upstream and downstream operations. Announced in November 2019, the project is being implemented over four phases as part of the company’s digital acceleration program to embed advanced digital technologies across its operations. Phase 1 covers the modeling and monitoring of 160 turbines, motors, centrifugal pumps, and compressors across six ADNOC Group companies. All phases of the project are expected to be completed by 2022 and will enable monitoring of up to 2,500 critical machines. Using artificial intelligence (AI) technologies including machine learning and digital twins, the company’s predictive maintenance platform helps with equipment stoppages, reduces unplanned equipment maintenance and downtime, increases reliability and safety, and is expected to deliver maintenance savings up to 20%.
Al-Ghaferi, Mohamed Mubarak (ADNOC Onshore) | Al Janahi, Mohammed Ibrahim (ADNOC Onshore) | Al Jaberi, Fawzi Omar (ADNOC Onshore) | Albadi, Mohamed Mubarak (ADNOC Onshore) | Al Ameri, Mohamed Saeed (ADNOC Sour Gas) | Al Hosani, Ayesha Ibrahim (ADNOC Onshore) | Shivade, Vijay (ADNOC Gas Processing) | Zaidan, Hassan Khamis (ADNOC Onshore) | Abual-Haj, Osama Diab (ADNOC Onshore) | Konkati, Sarath (ADNOC Onshore)
ADNOC Onshore is operating Habshan gas production field on behalf of Abu Dhabi National Oil Company (ADNOC). The gas reservoir production zones were developed under different project phases. The field has 250 gas (production and injection) wells, which are placed and located in approximately 1200 square kilometers. All gas wells are designed to have SCADA system to monitor, operate and control the wellhead control systems.
Current practice within ADNOC Onshore is to carry out monitoring for Cathodic Protection (CP) of well casing and Chemical Injection (CI) surveys on quarterly basis, this is carried out by mobilizing entire crews physically (visiting every single location) and reporting findings/conditions in order to carry out preventive maintenance and necessary repairs.
The aim of the project is to establish a remote monitoring system utilizing the existing Supervisory Control and Data Acquisition (SCADA) setup in order to monitor the applied corrosion controls, CP and CI injection systems. Based on the implemented modification, essential information was collected, intensive review and analysis were performed and revealed that the system is functioning perfectly as per the operation's requirement for both (CP & CI).
This approach forms a vital aspect of the integrity management of the asset by monitoring the effectiveness of the applied corrosion controls, in addition, the implementation will help Operations to optimize resources, efficiently monitor, maintain, and ensure safety of the facilities and its integrity. Moreover, the implemented method will drastically reduce the associated travelling risk, limiting exposure to the harsh environment (Desert) and potential cost saving.
Offshore natural gas fields are normally developed based on multiphase flow. One of the key challenges for such flow lines may be the risk of gas hydrate formation. This risk can be mitigated by injecting Mono Ethylene Glycol (MEG) into the flow line as a thermodynamic hydrate inhibitor. Due to the large volumes of costly glycol required and the desire to minimise the environmental footprint, the glycol is regenerated on topside or onshore facilities. Presence of salts in the MEG systems make it more challenging to operate them and having full control over the chemistry within the MEG system is key to have successful operation. Today chemistry control within MEG system is largely done by manual sampling and lab analysis as online analysers are either not available or not qualified for the service. Having robust online analysers that can measure water, MEG, pH stabiliser and dissolved salts will minimize these challenges and enable remote operations of the MEG systems.
A Digitalization platform enabling condition monitoring and remote operations system to optimise performance and maintenance efforts on the MEG Regeneration and Reclamation Systems is being developed. The system collects digital input from sensors, analysers, instruments and controllers on the onshore or offshore assets to monitor system behaviour. The uniqueness of the approach to remote operations is our unparalleled process and chemistry expertise in combination with our in-house data science team to produce a system-wide view of the MEG Regeneration and Reclamation system. Current and historical data from MEG Regeneration system are ingested into the data platform, and through custom algorithms, provides full visualisation of the system performance and condition monitoring of critical components within the system. The operating conditions are characterized to reduce downtime and operating costs and maximise production.
Online monitoring of the composition of rich- and lean MEG and formation water breakthrough can improve predictability of the scaling tendency and operation of the MEG plant. This can be achieved by having a qualified set of online analysers that can measure MEG, water and ionic composition online. With this enhanced visibility of the performance and predictive analysis, the need for site visits and troubleshooting efforts can be reduced and repeat failures and unplanned downtime can be prevented.
The digitalization platform and work approach has already been successfully implemented on Sulphate Removal Units/Water Injection Technologies but are new to MEG systems. Qualification programs of critical parameters such as MEG content, chloride and divalent cation ion measurements are being carried out in parallel as part of the digitization efforts.
Selected results from testing of online analysers and the key features from the digitalization platform are presented in this paper.
An online analyser has been tested for simultaneously measuring MEG, water, organic acids and MDEA. The analyser was able to measure these concentrations with a deviation (difference in wt.% concentration) of 0.3 to 0.5%. The impact of relevant process temperature on the MEG and water analysis was minimal.
Similarly, an online analyser has been tested for measuring chloride and divalent ions in presence of MEG. The limit of detection for chloride was about 3 to 9 ppm depending upon the measurement time. The limit of detection for Ca2+and Ba2+ was 3-9ppm and for Sr2+ and Fe2+ was 0.1 to 0.5 mg/l.
Giunta, Giuseppe (Eni SpA, Development Operations & Technology) | Bernasconi, Giancarlo (Politecnico di Milano, DEIB Department) | Giro, Riccardo Angelo (Politecnico di Milano, DEIB Department) | Cesari, Simone (Eni SpA, Development Operations & Technology)
In recent years, big data technologies have paved the way for digital transformation in oil and gas industry. Multi-domain measurements are collected by advanced sensor systems and processed using data-driven approaches, allowing to derive constitutive relations between the operational status of the asset and the measured variables. In addition, historical pressure measurements can be exploited for advanced pipeline monitoring. This paper presents a methodology, applied to a case history, where legacy data are repurposed and employed both to track pump health and to enhance the digital conversion. The dataset consists of past pressure signals collected by Eni for several years at the pumping terminal of a crude oil transportation pipeline, which has a length of 100 km and 16" diameter pipes, located in Italy. Pressure transients' variance, kurtosis and variation range, computed on appropriate window lengths, are fed to an unsupervised clustering procedure based on a Gaussian Mixture Model (GMM), which automatically identifies four clusters. An expert analysis of the labeled data reveals that each cluster corresponds to a well-defined and different pump operational mode, namely: standby (pumps off), transition (pumps switching on/off), normal (line flowing) and anomalous. The latter mode is connected to a high value in the pressure transients' variance and kurtosis: during such regime, pump maintenance logs report a failure and replacement of a system part. Interestingly, the anomalous condition starts to show up several days before the actual part replacement. The proposed case history reveals the potentiality of: adding value to legacy data, as they can be reprocessed, tagged and used as supervised examples in the training phase of new data-driven procedures; comparing, merging and complementing monitoring strategies of assets at different digitalization stages; aiding the development of predictive maintenance strategies.
Traditional methods of inflow profile monitoring are not always effective, especially when tight reservoirs are considered. One of the most progressive solutions is the use of marker technologies based on the markers' selection and subsequent identification in fluid taken at wellhead [
In the context of high hydrocarbon price volatility on the global market and worsening resource structure an increasingly greater attention is paid to the search of effective and economically sound tools for production and exploitation process management and control, including in horizontal and directional wells.
Conventional PLT methods applied in extended reach drilled (ERD) wells have a number of limitations related to data relevance and well bore accessibility. The alternative method is deployment of tracer-based material while well completion process. This enables a stream of downhole data on demand without needs of well intervention using Coiled Tubing or Tractor services.
This paper describes an approach of deploying the dynamic tracer-based production logging monitoring systems as a part of well completion equipment. Special cassettes attached to slotted liners or ICV/ICDs carry out advanced polymeric composition for 3-phase monitoring for oil, water and gas, including off-shore project with extended reach wells (ERD).
The maritime industry is facing a period of major disruption, with its effects not confined to the physical world. Even before the COVID-19 pandemic, recent years saw our industry experience extreme instability, with global oil and gas markets declining. We have seen increasingly unpredictable Brent prices, and the oil and gas services sector has suffered significantly. This has resulted in a structural change to the market, which in turn requires the industry to rethink and reinvent the business model. This means reducing costs and challenging the status quo and establishing more of a partnership with clients to add value through distinct, more tailored services and solutions. A critical factor in this is the implementation of digital technology and the use of data as a direct business enabler.
The realisation that digital tools and technology have the ability to impact client relationships, business models and vendor relationships is one that P&O Maritime Logistics (POML) recognised early. Despite our status as a historical business, with over 180 years of maritime history under our belt, we are also a business that looks to constantly improve and deliver a difference which drives value across all seven continents. When others see barriers, POML sees opportunities, and none appear larger than the opportunities presented by embracing the digital revolution.
Whilst the maritime industry has traditionally lagged behind some other industries in the application of technology, and there was no doubt in our minds that the time is right for a change and to disrupt conventional ways of working. To achieve this, P&O Maritime Logistics (POML) has invested heavily in systems to collect and process data in real-time from our offshore operations, while also connecting our offshore and onshore personnel as we expand our fleet. Such measures remove the need for many manual processes, empowering our offshore organisation and creating long-term cost efficiencies. As we navigate the COVID-19 pandemic and beyond, a core focus for our business will be the further optimisation of offshore logistics for energy companies, with technology at the heart of this.
We are aiming to move up the value chain in the global energy industry through a growing portfolio of cost-effective and innovative services. As our clients' demands evolve, we are adapting our service-led offering to stay at the forefront of industry needs and remain as the preferred provider of marine logistics services and solutions. We have increased our focus on providing end-to-end digital logistics solutions and have proven our ability to deliver large-scale, bespoke services, in collaboration with our customers and partners.
The Offshore Support Vessel (OSV) survivors of the recent downturn included those organisations that were willing and able to make changes to reset their businesses and strategies to suit a new market. Any transformation is challenging, and changing the mindset of our entire organisation as well as protecting the bottom line can put significant strain on an organisation. A key differentiator is the embracement of IT as a direct business enabler. Digital is disrupting companies from their service offering through to their operations and maintenance. From customer dashboards providing real-time insight into the state of their operations, to the use of Internet of Things (IoT) to learn more about the state of our vessels, and moving IT to a driver of both the top line and of cost reductions.