OffshoreLytics

Experiment description

The offshore oil and gas exploration and production is one of the industries that has changed drastically in terms of technological developments and operation styles in the past decade, esp. due to very harsh operating condition(weather,  environment). It requires a continuous process improvement, which will only be possible through appropriate new technologies that are exploiting new opportunities for the optimization.

Offshore process monitoring in the drilling process are generating GBs of(useful) data daily, in this experiment, Rolloos main goal have been to perform a feasibility study, Proof of Concept, to test the suitability of MIDIH data analytics Platform for resolving monitoring of alarm situations, esp. to enable(proactive) detection of the  new alarm situations. The main result of this experiment is the D2LabRig Portal, based on MIDIH industry data analytics platform, which visualizes OffshoreLytics service. The Portal/service provides an automatic overview of the dynamics in the realization of the rig operation/processes and the main task is to enable an automatic analysis and reporting of important processes in a rig operation scenario. The service uses rig sensor data to automatically generate an objective description of the performances (KPIs) of the drilling process using an advanced hybrid analytics approach. The focus is on understanding the behavior of the drilling process, to be able to detect situations (and their causes) when the process behaves in a suboptimal way.

Figure 1. High level architecture of the experiment.

Figure 2. Mapping of the experiment on the MIDIH architecture

As presented in Figure 2, data goes directly from the real world, through D2Twin, in OffshoreLytics service. This is a part of Smart Product environment. It belongs to the APACHE line.

D2LabRig Portal is based on the data provided by the OffshoreLytics service. D2Twin is mediator for this communication

Technical impact

The usage of MIDIH components was very successful, both from the point of view of the easiness of usage and the effectiveness of services (D2Twin). Data-driven process monitoring and control (as implemented in OffsoreLytics service) can be applied in various use cases, esp. for the domains where the processes are ill defined. Test were performed to validate completeness, efficiency and the accuracy of created data-driven process model, which fulfilled all experiment KPIs.

Economical / Business impact

During the experimentation, it become clear that the provided service for automated reporting as well as the Portal can be used in various domains. For the near future Rolloos has agreed to work with 1 existing customer that has granted Rolloos the opportunity to validate it’s current data pipeline on two existing drilling rig for which all real time data acquisition is supported by Rolloos.

For Rolloos, the main focus areas will be to provide the following services and integrations:

• Performance analysis: Post well analysis tool to identify well performance on historical data
• Reporting service: Add Daily KPI to existing Rolloos drilling reporting service
• Roll@caster: Deliver drilling KPI on Edge computation device
• Rolloos Redzone Services: combine drilling performance KPI output with Deep learning vision based performance tools

By having an automated process that is consistent across all the drilling fleet, Rolloos will be able to offer a service that will help identify hidden lost time efficiency’s utilizing digital solution and reducing time spent by manual inputs.