Overview
Data collection is a time-consuming process on offshore drilling rigs. Staff can take days to complete the task manually with poor weather conditions and unstable internet connection. This inefficiency is not only reflected in data inaccuracies but also in rapid resource exhaustion.
To view the data after the initial data collection, users would have to connect their computer to a stable internet connection, pass through system security, and enter a digital twin environment in remote test operation settings like onshore offices. Since data can only be viewed by a limited number of users, any changes made to the data require collaboration and equal efforts from offshore staff and the team onshore.
We collaborated with our sister company, Seven Peaks Norway (Formerly Apphuset), and an information technology service provider based in Norway to build dynamic drilling control and monitoring systems for a major Oil and Gas enterprise client’s internal use and external application. Together, we embarked on a 4-year journey to digitally transform operations and improve work efficiency.
Our Solution
Our team developed two entirely new frontend systems to ensure real-time data monitoring and historical view displays happen concurrently and on the same screen. We applied configurable templates to confirm that features show up in full view for our client’s internal staff and on-demand for their customers.
The team maintained a consistent standard for data privacy by integrating a built-in multi-tenant system which makes it impossible for external parties to access information without permission. To make it more convenient for the end-users to get hold of relevant data, we enabled real-time access to historical playback and installed automatic system event detection that allows users to create tasks independently.
Our Approach
We kickstarted the project by carrying out product design discovery in order to make sense of our client’s business functions, operations, target customers and end goals. We then moved on to calculate project lead time before creating a proof of concept and conducting technical implementation analysis.
Next, we entered our 2-week sprints where each developer was assigned different tasks, resources and deadlines. We began by integrating with a controlled legacy system from the cloud and later extracted data from the legacy system.
The features that were developed would be fed into the CI/CD system, where any changes in code were integrated into a shared source code repository. To complete the final steps of the process, we deployed the end products into the customer test environment to ensure their optimal functionality. Data would later be sent to the cloud and visualized on screens upon user requests.
Challenges to Overcome
1. Achieving Security Compliance
The rig infrastructure follows a Purdue model, a theoretical framework that separates offshore industrial control system networks from our client’s onshore network and any internet connection, to prevent cyberattacks. This was the initial issue our team faced getting into the project. To accomplish the goal, our team had to come up with a solution to gain internet access.
Our team’s solution was to introduce a new agent at level-3 technical network that hops over reverse proxy to internet-based services from offshore networks. We started integrating a module in the level-3 network for data to pass through the level-2 network. Then, we aggregated and preprocessed data into simple, usable forms for them to later be analyzed and transferred onto the cloud.
2. Experiencing Frequent Internet Disruptions
The North Sea’s poor weather condition was causing unstable internet connectivity and frequent connection loss on the oil rigs. It was not uncommon for our team to regularly experience internet disruptions which can sometimes take longer than a few hours to resolve. This immensely affected our historical data transmissions to the cloud system with information uploaded every other 500 milliseconds.
Initially, our team solved this problem by buffering the data in memory but quickly realized that it would eventually run out of storage. We resorted to entering those data to the local file system for a more appropriate fix. Once the system was back online, we prioritized uploading those sets of files to ensure that no data was lost in the process.
3. Uploading Data with Insufficient Bandwidth
Another challenge we faced was the loss of bandwidth due to personal usage. For the team working on the rig, this hindrance made it increasingly difficult to upload large quantities of sensor readings (10,000+). To solve this, we came up with a bandwidth saving solution to optimize the amount of data we needed to upload.
After we examined the data and identified less-static variables like temperature, we got together to develop a tolerance boundary system. Our newly built system operates by analyzing and uploading values that exceed the maximum threshold. To prevent malignant bugs from entering the data pipeline, we developed an end-to-end testing to simulate the rig environment and control data entry.
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Sekal
Sekal is a leader in drilling automation software for the oil and gas industry. Their advanced digital solutions use real-time dynamic modeling to optimize drilling performance, increase safety, and drive the transition to autonomous operations.
