IoT Implementation on Artificial Lift System in the KS Brownfield in South Sumatra Indonesia

Hidayat, Azis; Sujai, Ahmad; Aryadi, Yuzar; Fathurachman, Ahmad

doi:10.2118/196335-ms

SPE/IATMI Asia Pacific Oil &Amp; Gas Conference and Exhibition 2020

DOI: 10.2118/196335-ms

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IoT Implementation on Artificial Lift System in the KS Brownfield in South Sumatra Indonesia

Azis Hidayat¹,

Ahmad Sujai²,

Yuzar Aryadi

et al.

Abstract: The world industrial revolution has entered industry 4.0, where cyber-physical systems monitor physical processes over the internet of things (IoT) and cloud computing. SCADA is one of area where the industry 4.0 can be implemented, which could swift the way of work to monitor and control wells production from human dependent to real time data dependent. However, the implementation of SCADA technology is usually constrained by expensive cost. In the KS brownfield, ESP is the major artificial lif… Show more

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Cited by 3 publications

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Development of Real-time Monitoring System in Organic Rankine Cycle Operation of Lahendong Geothermal Field

Wibowo

Aji

Cahyadi

et al. 2020

SPE Annual Technical Conference and Exhibition

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Geothermal resources in Indonesia are commonly located in spread mountain area and some scattered in small islands, such as in Nusa Tenggara and Maluku province. Small scale geothermal power plant with a wellhead type may be required for some geothermal field areas. In operation and maintenance of geothermal power plant usually need high skilled personnel. The real-time monitoring system (RTMS) becomes a promising option for performance analysis and optimization from a remote monitoring room. The performance engineer may execute some small scale power plant in different project sites. The monitoring needs the data variables related significantly to the production of power output. Therefore, finding an attractive-interface, and related variables data of power output, become an interesting issue in performance monitoring. Lahendong organic Rankine cycle (ORC) power plant in North Sulawesi Indonesia, with a capacity of 500 kW, has implemented the RTMS. RTMS data, starting from the sensor reading up to the programmable logic controller (PLC) as a local data collector, transferred to the server (which placed in Germany) via the connection hub. From the server, the data stored on the database and visualize on the human-machine interface (HMI). The variables of the RMTS have been analyzed. The study includes analyzing the scatter-plot of the variables, plotting of the time variables, and applied the Pearson coefficient correlation (PCC) to discover the most related variables to the power output. The variables include brine inlet temperature, brine inlet pressure, hot water inlet temperature, hot water inlet pressure, and power output during the three months. The result, the monitoring of the Lahendong ORC power plant gives positive feedback to the user, with interactive visualization data. The feedback shows that hot water temperature has the most robust correlation to the power output of the Lahendong ORC power plant with 0.91, close to 1 for PCC analysis. In the future, machine learning analysis will be applied to RTMS on Lahendong, so that it will increase user experience and sharpening data analysis. The relocation of the server from Germany to Indonesia will be done to add decision-making features. Expectedly, this paper can be a reference to other power plants and fields that apply RTMS as remote monitoring, taking into consideration the remote location of the geothermal field.

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Development of Real-time Monitoring System in Organic Rankine Cycle Operation of Lahendong Geothermal Field

Wibowo

Aji

Cahyadi

et al. 2020

SPE Annual Technical Conference and Exhibition

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A Comprehensive Review of the Fourth Industrial Revolution IR 4.0 in Oil and Gas Industry

Temizel

Canbaz

Aydın³

et al. 2021

SPE/IATMI Asia Pacific Oil &Amp; Gas Conference and Exhibition

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Digital transformation is one of the most discussed themes across the globe. The disruptive potential arising from the joint deployment of IoT, robotics, AI and other advanced technologies is projected to be over $300 trillion over the next decade. With the advances and implementation of these technologies, they have become more widely-used in all aspects of oil and gas industry in several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still trying to adapt to IR 4.0. This paper examines the value that Industry 4.0 brings to the oil and gas upstream industry. It delineates key Industry 4.0 solutions and analyzes their impact within this segment. A comprehensive literature review has been carried out to investigate the IR 4.0 concept's development from the beginning, the technologies it utilizes, types of technologies transferred from other industries with a longer history of use, robustness and applicability of these methods in oil and gas industry under current conditions and the incremental benefits they provide depending on the type of the field are addressed. Real field applications are illustrated with applications indifferent parts of the world with challenges, advantages and drawbacks discussed and summarized that lead to conclusions on the criteria of application of machine learning technologies.

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Artificial Lift Real-Time Monitoring Digitalization Method: An Advanced Approach with Artificial Intelligence to Achieve Efficient Well Surveillance by Utilizing SCADA

Putra,

Tanjungsari,

Edyawan

et al. 2023

Day 2 Wed, October 11, 2023

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In Block X, there are a limited number of engineers and a vast number of wells that require to be monitored on a daily basis. Before 2018, engineers must visit each well to survey and monitor its status. This process proved to be inefficient due to the shortage of engineers which was aggravated by arduous journeys to remote areas, and long response time during test line leakage. To improve the quality of surveillance and artificial lift systems, Medco E&P proposed the installation of Supervisory Control and Data Acquisition (SCADA) monitoring systems. SCADA was installed using Global System Mobile Communication (GSM) modem in ESP wells while SRP wells used Rod Pump Controlled modem. Data from both artificial lift wells is sent automatically to the user's platform through the installed system. By implementing this SCADA system, the data can be acquired more efficiently without the need for engineers to be present in the field. This leads to an effective surveillance monitoring activity where well status can be determined remotely and shorten response time when problems arise. Since the installation of the SCADA system, the average loss potential oil of ESP wells was decreased to around 24% while the down duration was decreased by 33%. These percentages correspond to a savings of $20,000 per month in LPO (Loss Potential Oil) after the implementation of SCADA. The test line leakage problem can be solved through creating a virtual metering feature using machine learning based on the SCADA data acquired. This virtual metering is used to predict the liquid rate of each well using already existing well parameters without the need for well testing. The SCADA data can be further used for further analysis to prevent Sucker Rod Pump (SRP) pump failure and increase lifespan of the pump by determining SRP Unit Balance.

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IoT Implementation on Artificial Lift System in the KS Brownfield in South Sumatra Indonesia

Cited by 3 publications

References 2 publications

Development of Real-time Monitoring System in Organic Rankine Cycle Operation of Lahendong Geothermal Field

Development of Real-time Monitoring System in Organic Rankine Cycle Operation of Lahendong Geothermal Field

A Comprehensive Review of the Fourth Industrial Revolution IR 4.0 in Oil and Gas Industry

Artificial Lift Real-Time Monitoring Digitalization Method: An Advanced Approach with Artificial Intelligence to Achieve Efficient Well Surveillance by Utilizing SCADA

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