C. Leach, Guangzhao Zhou, Veerabhadra S. Denduluri, G. K. Wong, R. Krishnamoorti, A. Prosperetti
{"title":"A New Fundamental Understanding of Gas in the Drilling Riser","authors":"C. Leach, Guangzhao Zhou, Veerabhadra S. Denduluri, G. K. Wong, R. Krishnamoorti, A. Prosperetti","doi":"10.4043/31248-ms","DOIUrl":"https://doi.org/10.4043/31248-ms","url":null,"abstract":"\u0000 The work described here originated from the tragic and ultimately environmentally catastrophic event at the Macondo well in April 2010. The first part of the paper addresses the causes for the sudden and often destructive ejection of hydrocarbons from a riser when a gas kick escapes timely detection. The approach differs from previous work on the subject and provides a realistic understanding of the sequence of events responsible for the phenomenon. The focus is on the crucial few minutes and seconds prior to the sudden eruption of gas and provides a quantitative illustration of the extreme rapidity of the ejection which leaves no time for a drill crew to adopt mitigation measures. It is shown that, in many cases, a back-pressure applied at the top of the well can be beneficial. The second part of the paper describes a novel method for the detection of gas which relies on the measurement of pressure differences along sections of the riser. These data are sensitive to the mean density of the fluid in the section and can therefore detect the presence of free gas. Laboratory experiments supporting the idea are described. Proper signal processing can be developed which may be able to allow for automatic mitigation measures to be taken in the event of an otherwise undetected gas influx approaching the surface.","PeriodicalId":11084,"journal":{"name":"Day 4 Thu, August 19, 2021","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85919087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rodrigo Chamusca Machado, Fabbio Leite, Cristiano Xavier, Alberto Albuquerque, S. Lima, Gustavo Carvalho
{"title":"Development of Failure Prediction Models for Subsea Blowout Preventers Using Data Analytics and AI","authors":"Rodrigo Chamusca Machado, Fabbio Leite, Cristiano Xavier, Alberto Albuquerque, S. Lima, Gustavo Carvalho","doi":"10.4043/31027-ms","DOIUrl":"https://doi.org/10.4043/31027-ms","url":null,"abstract":"\u0000 \u0000 \u0000 This paper presents how a brazilian Drilling Contractor and a startup built a partnership to optimize the maintenance window of subsea blowout preventers (BOPs) using condition-based maintenance (CBM). It showcases examples of insights about the operational conditions of its components, which were obtained by applying machine learning techniques in real time and historic, structured or unstructured, data.\u0000 \u0000 \u0000 \u0000 From unstructured and structured historical data, which are generated daily from BOP operations, a knowledge bank was built and used to develop normal functioning models. This has been possible even without real-time data, as it has been tested with large sets of operational data collected from event log text files. Software retrieves the data from Event Loggers and creates structured database, comprising analog variables, warnings, alarms and system information. Using machine learning algorithms, the historical data is then used to develop normal behavior modeling for the target components. Thereby, it is possible to use the event logger or real time data to identify abnormal operation moments and detect failure patterns. Critical situations are immediately transmitted to the RTOC (Real-time Operations Center) and management team, while less critical alerts are recorded in the system for further investigation.\u0000 \u0000 \u0000 \u0000 During the implementation period, Drilling Contractor was able to identify a BOP failure using the detection algorithms and used 100% of the information generated by the system and reports to efficiently plan for equipment maintenance. The system has also been intensively used for incident investigation, helping to identify root causes through data analytics and retro-feeding the machine learning algorithms for future automated failure predictions. This development is expected to significantly reduce the risk of BOP retrieval during the operation for corrective maintenance, increased staff efficiency in maintenance activities, reducing the risk of downtime and improving the scope of maintenance during operational windows, and finally reduction in the cost of spare parts replacementduring maintenance without impact on operational safety.\u0000 \u0000 \u0000 \u0000 For the near future, the plan is to integrate the system with the Computerized Maintenance Management System (CMMS), checking for historical maintenance, overdue maintenance, certifications, at the same place and time that we are getting real-time operational data and insights. Using real-time data as input, we expect to expand the failure prediction application for other BOP parts (such as regulators, shuttle valves, SPMs (Submounted Plate valves), etc) and increase the applicability for other critical equipment on the rig.\u0000","PeriodicalId":11084,"journal":{"name":"Day 4 Thu, August 19, 2021","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82037773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shunsaku Matsumoto, V. Jaiswal, T. Sugimura, Shintaro Honjo, Piotr Szalewski
{"title":"Mooring Integrity Management through Digital Twin and Standardized Inspection Data","authors":"Shunsaku Matsumoto, V. Jaiswal, T. Sugimura, Shintaro Honjo, Piotr Szalewski","doi":"10.4043/31036-ms","DOIUrl":"https://doi.org/10.4043/31036-ms","url":null,"abstract":"\u0000 This paper presents a concept of a mooring digital twin frameworkand a standardized inspection datatemplate to enable digital twin. The mooring digital twin framework supports real-time and/or on-demand decision making in mooring integrity management, which minimizes the failure risk while reducing operation and maintenance cost by efficient inspection, monitoring, repair, and strengthening. An industry survey conducted through the DeepStar project 18403 identified a standard template for recording inspection data as a high priority item to enable application of the digital twins for integrity management. Further, mooring chain was selected as a critical mooring component for which a standard inspection template was needed. The characteristics of damage/performance prediction with the proposed mooring digital twin framework are (i) to utilize surrogates and/or reduced-order models trained by high-fidelity physics simulation models, (ii) to combine all available lifecycle data about the mooring system, (iii) to evaluate current and future asset conditions in a systematic way based on the concept of uncertainty quantification (UQ). The general and mooring-specific digital twin development workflows are described with the identified essential data, physics models, and several UQ methodologies such as surrogate modeling, local and global sensitivity analyses, Bayesian prediction etc. Also, the proposed digital twin system architecture is summarized to illustrate the dataflow in digital twin development andutilization. The prototype of mooring digital twin dashboard, web-based risk visualization and advisory system, is developed to demonstrate the capability to visualize the system health diagnosis and prognosis and suggest possible measures/solutions for the high-risk components as a digital twin's insight.","PeriodicalId":11084,"journal":{"name":"Day 4 Thu, August 19, 2021","volume":"326 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80365089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. McLachlan, Changlih Ee, J. Veen, Fabien Cochet, Daniele Tomassi, T. Olivieri, Jeff Stroh
{"title":"Requirements Management for Data Driven Requisitions","authors":"D. McLachlan, Changlih Ee, J. Veen, Fabien Cochet, Daniele Tomassi, T. Olivieri, Jeff Stroh","doi":"10.4043/31231-ms","DOIUrl":"https://doi.org/10.4043/31231-ms","url":null,"abstract":"\u0000 \u0000 \u0000 Systems engineering techniques, particularly requirements management, are critical to realizing the value of digital transformation to improve capital project delivery. Drawing on the results of a case study, this paper will demonstrate the value of using digital requirements management to exchange information through a project lifecycle, specifically showing benefits in the integrity of data transfer; more efficient procurement lifecycle; more robust deviation management; and bidirectional traceability of requirements, including full visibility and end to end verification and validation.\u0000 \u0000 \u0000 \u0000 A requirement is a capability to which a project outcome (product or service) should conform, and the purpose of requirements management is to ensure that an organization documents, verifies and validates these capabilities. In this case study the operator provides their technical specifications in the form of requirements. These requirements are then imported into the EPC's PLM platform, where they are supplemented with additional information from the EPC's engineers to create a requirements-based requisition package. This is then transmitted to the equipment supplier, where it is reviewed and, for the purposes of the case study, reviewed for completeness. To test the ability to identify changes and deviations, the EPC engineer modified the requirements and the file was transferred to both the operator and equipment supplier to ensure the changes were transferred and were identifiable. The case study also demonstrates how verification activities (testing, commissioning, etc.) can be linked to requirements; passed through the supply chain and be modified to capture changes to the status of the activity (such as test results).\u0000 \u0000 \u0000 \u0000 The case studies described show how requirements can be exchanged between operator, EPC and equipment supplier without any loss of data. It will also show how this approach allows a data driven approach, as opposed to a document driven approach, to be deployed in the requisitioning process, which could facilitate substantial reduction in the procurement lifecycle. This is achieved by removing extraneous information exchanged between the companies; the removal of swivel chair solutions, where data is extracted from one system and transferred to another; and expediting the bid evaluation stage. Finally, the case study will demonstrate how this approach could be extended beyond the purchase order to provide a direct link between specific requirements and testing (FATs) or commissioning activities, which facilitates a more efficient process for verification as well as ensuring a digital record of the entire lifecycle of a package. The case study highlighted the importance of aligning data model and developing workflows, these findings are captured in the lessons learned section and have been shared with the International Association of Oil and Gas Producers (IOGP) Requirements Digitalization Task Force (RDTF).\u0000 \u0000 \u0000 \u0000 The pap","PeriodicalId":11084,"journal":{"name":"Day 4 Thu, August 19, 2021","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82355837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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