Cairn Oil & Gas uses IT to win one business test after another

Cairn Oil & Gas is India’s largest oil and gas exploration and production company. It currently contributes 25% to India’s gross domestic product (approximately 28.4 MMT) and accounts for 50% of GDP. The company plans to spend 3,16.09 kroner ($ 31.6 billion) over the next three years.

The oil and gas industry is currently facing three major challenges.

Sandy Gupta, chief digital and information officer at Cairo Oil and Gas, is using state-of-the-art technology to overcome these challenges and achieve business goals. We have adopted a value-added approach to deploying technological solutions. “We are working with a number of original manufacturers and service providers to deploy large-scale projects in the high-cost chain,” he said.

Reduce operating costs by drones, AI and edge computing

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The oil and gas industry has experienced significant fluctuations in commodity prices and geopolitical conditions. In such a case, it will be crucial to control costs for the business.

Ongoing oil production is based on uninterrupted power supply. But managing transmission lines is a costly, resource-intensive task. That means managing the 250-mile[250 km]power line in 3,111 square kilometers. They supply power to the company’s Mangala, Bhagayam and Ishwaria gas stations and the Rajasthan gas fields in Rajasthan.

To reduce operating costs, the company decided to use drones. The images captured by the drones work in an AI image-recognition system. The system investigates potential damage to power lines, predicts potential failures, and suggests preventive measures, thus making informed decisions rather than judging the operator.

“Algorithms such as convection neural networks are trained on images taken when the above lines are in good condition.

This is a service-based contract between Kair and the maintenance provider, which is monitored every two years for 220 kV power lines and 500 kV power lines.

“The average time between crashes has increased from 92 to 182 days since the drone-based inspection took place. This has reduced oil waste to 2,277 barrels per year, saving an estimated 12 crores.” [₹120 million]. Because it allows the staff to carry out maintenance work more efficiently, a smaller team can work more efficiently, and the required manpower will be reduced, ”says Gupta.

The location of remote operations combined with large amounts of data (Kern generates up to 300 GB of data per day) makes it easy to use devices based on the edge of the oil and gas industry.

Critical measurements with smart edge devices are stored and performed at remote locations. The devices are installed in the field where the MQTT protocol sends data to the cellular network connection. They store up to 250GB of data on the Microsoft cloud and perform analytics and intelligent alerts using machine-learning algorithms.

In the absence of these devices, the data is generated by transporting it to remote data centers and shutting down network bandwidth. Because low bandwidth is sufficient to handle large amounts of data, edge computing can help reduce our IT infrastructure costs. These engaged devices are monitoring critical operating parameters such as pressure, temperature, emissions and flow rates. The possibility of edge computing requires a network with high bandwidth, which is about 2X of the current network cost, ”Gupta said. “This has implications for the health and safety of our staff and equipment.”

Reduce lead times with cloud-based strategy

The oil exploration process takes about three to five years and requires a great deal of capital. Most of these three to five years will be spent on modeling models that require huge computational power by petrochemical technicians (geologists, geophysics, petroleum engineers and reservoir engineers).

The petrotechnical process involves evaluating groundwater reservoir characteristics to identify the location of the wells. These workflows are carried out by a number of software applications by petrotechnicians, which help to determine the location and direction of the wells to be drilled.

“Capital allocation and planning for future exploration has become even more dangerous because of the long lead. It is important to increase computer capacity to achieve our goals. “This migration has removed the computational capacity limits on campus. As a result, there is a 30% reduction in oil prices in the first place. ”

Managing analysis by predicting product decline

Cair has a large volume, type and speed of information coming from various sources in production, navigation and management. “Using this information, we have deployed several large-scale projects, including adjusted forecasting, model forecasting control and water storage management in several areas,” Gupta said. Model Predictive Control (MPC) is a technology that monitors the performance of various parameters and then operates to achieve maximum efficiency in a particular region, while maintaining the limits within the system.

The core of this dish is a business intelligence that uses dashboards to drive critical practical insights. “Dishan’s philosophy is to make the right information available to the right people at the right time. We want to avoid file-based data sharing and reporting because it takes time to create these reports. We are connected to a Microsoft Power BEE environment where reports can be generated, ”Gupta said.

Disha was developed in a mixed mode by an internal team and an analytics provider over three years. Provides more than 200 custom dashboards, including a well-controlled dashboard, product improvement dashboard, CEO and CCO dashboard and rig schedule.

“Information is now easily and quickly accessible in an interactive format within the organization. “For example, we use Disha oil and water to monitor the measurement and output of an electronic underwater pump. It helps us to track the results of the MPC implementation. “This individual will be a low-level code platform that allows teams to build their own solutions,” says Gupta. Some of the initiatives include artificial lift monitoring, well monitoring and good test verification, ”Gupta said.