In assets like Shushufindi, water handling has become a challenge to achieve a proper field management. Apart from increasing water cuts, longevity and ullage of the processing facilities have turned into a challenge to sustain production and reduce lifting costs. A digital solution was implemented to allow predictive analysis for horizontal pump failures and line plugging as well as forecasting of injection rates on real-time to improve the efficiency of operations to maximize productivity. Numerous failures occurred in the water handling system due to the lack of real-time monitoring or fast detection. This caused around sixty ESP's to be shut-in every year, triggering production losses. Hardware for data collection in selected points and customized digital workflows using data analytics and machine learning processes were developed and implemented so that with the help of edge computing we were able to predict failures and estimate injection rates on real time. Using the connectivity provided by a satellite system, SCADA's optical fiber and an operations monitoring platform, the variables are now monitored on real time to make early identification of events, give a rapid response and to optimize the production of the field. The Northern Flow Station, located in the most prolific area of the field and where the water flooding scheme has the highest relevance was selected to implement the digital pilot. The implementation of this digital initiative has shown outstanding results. Monitoring for the first time the data from the water handling system on real time and applying the engineering workflows (data analytics and machine learning) led us to reduce up to 76% of the time used in manual processing, 75% of the time for commuting and to reduce 1-ton CO2eq emissions per year. The time saved is now used to improve other engineering workflows equally important to increase the productivity of the field. Due to the early identification of events, the prediction of potential failures and a timely response previous functional failure, the Operational team can reduce the deferred production associated to the Electrical Submersible Pumps shut-ins, which for the previous years represented 100,000 barrels of oil (~$2.4MM revenue for Shushufindi Asset). In addition, such actions have contributed to extend the ESPs’ run-life, optimized maintenance costs and reduce lifting costs by 0.2%. This paper shows the selection criteria of the surface facilities and measurement of critical points for data gathering, the application of data analytics with edge computing and the development of an innovative digital solution in conjunction with the client and different disciplines. This case shows the benefits of digital mindset in any oilfield operations to optimize production and cost, potentiating the digital transformation path in the energy industry.
For more than 30 years, most of the fields in Ecuador have reached a high level of maturity that demands several operational and control challenges for multiple processes such as chemical injection, high gas volumes, water cut incremental among many other issues affecting the useful life of downhole equipment installed in the well or devices located on the surface. Furthermore, implementing digital solutions in a field also faces the challenge of allocating faster and agile solutions that add efficiency to production, but at the same time avoid or minimize deferred production for implementation. Fortunately, current digital technologies such as IoT and Edge Computing are combined with cloud applications, controllers and even software to connect and use unimagined solutions for the oil and gas industry. These controls make an easier, faster, and more reliable way guaranteeing the production integrity operations, while reducing carbon footprint and improving work-life balance. Operations case studies in Ecuador will be discussed including not only production engineering analysis but also production operations in the field with a major focus on asset surveillance. Both activities require time-consuming tasks such as field trips and well-by-well analysis, showing the transformation in the way we operate leveraging the use of data, promoting remote operations, and automating the workflows used within the production engineering department. The starting point of this implementation was the well surveillance workflow, carried out at the field level because there was no mature SCADA system. Thus, the Edge was implemented with capabilities based on Internet of Things (IoT) technology to connect the different elements of the production chain. Currently, more than 400 pieces of equipment have been connected to a unified platform, including electro-submersible pumping equipment (ESP), wells with Beam Pumping (BM), injector wells, injection pumps, high-pressure injection equipment, multiphase flow meters and others, which allow us to integrate data, perform real-time analysis and remotely control any equipment that is connected. The impact of this solution is the reduction of production losses by 9%, the reduction of field visits by 23%, the increase in the useful life of the equipment by 32% and the reduction of CO2 emissions by 22.6% in surveillance activities. On the other hand, the integration between the intelligence at the edge and the corresponding instrumentation allowed the creation of two tailored solutions. The first, to automate the annular gas handling process, and the second, to automate and optimize the efficiency of the chemical treatment. The tangible benefits of these solutions are: 12 gas handling equipment operating in the field, resulting in a 12% increase in production compared to wells that do not have the solution, chemical injection accuracy increased up to 99% and corrosion/fouling failures reduced by 50%. Using the benefits of IoT, different applications (more than 14) were implemented such as: flare monitoring and gas volume measurements, virtual flow meter, smart alarms, surveillance of portable multiphase flow meters (Vx Units), pumping equipment of high pressure (HPS) and monitoring and diagnosis of vibrations in rotating equipment
A novel solution was proposed in Ecuador to transition from reactive to a proactive way of working into a collaborative environment. This new workflow is supported by a portfolio of three production technologies that integrates live and historical information by combining the edge intelligence strength (for each production element connected to IoT platform) and the cloud insight to enhance the field operational efficiency. Technology that reduces carbon footprint and increases people’s efficiency through automation of repetitive tasks. The main challenge that required an integrated and smart solution was the existence of silos, meaning that all production chain elements were disconnected. The solution consisted of a portfolio of three technologies. First, connecting all production chain elements to one unique gateway and Edge platform: all data were consolidated to perform asset surveillance, monitoring, and controlling of electrical submersible pump (ESP) parameters from any vendor. Second, creation of an autonomous system aiming to avoid gas blockage on ESPs. Third, deployment of Production Engineering Orchestrator, fully completed and in continuous improvement, easing collaborative, day-to-day analysis for production, operations, and exploitation engineers We achieved remarkable results with Internet of Things (IoT) and cloud insights implementation; for instance, travel reduction of 18%, personnel efficiency increase (production operations 7% and surveillance engineers 25%), 47% events detection increase, 32% well uptime increase, and 2.14 t carbon dioxide emissions reduction (22.6%). Because of the outstanding results achieved from IoT adoption, new applications were deployed in other projects. With automated annular gas handling, production challenges related to high gas/oil ratio wells were solved. Solution consisted in delivering an automated ESP gas-handling process by using a securely connected, solar-powered skid to optimize well performance, production was increased by 12%, field visits reduced by 94%, and valves manipulation decreased by 97%. Other applications are also running in parallel, to expand the concept of intelligent asset solution. For the production engineering workflows orchestrator, the native implementation is completed, where the highest business impact workflows are included, such as smart production surveillance, waterflooding optimization and ESP surveillance. Insights are shown in "production overview". It is also possible to follow up oil and water producing wells, task modules, customized maps and graphs, sanity check processes, and well model calibration (including the paraffin curves). The integration of these three digital production technologies to improve artificial lift surveillance, production surveillance, and waterflooding optimization workflows is already deployed and showing tangible benefits. Currently, a mature field project is currently working in a collaborative environment, promoting a new proactive operational philosophy that avoids early pump failures, reduces downtime, field trips, personnel exposure due to the COVID-19 pandemic and supports the environmental commitment towards the carbon footprint reduction
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