Artificial intelligence (AI) and machine learning (ML) have been integral to the operations of the oil and gas industry for many years. These technologies have helped in modeling reservoirs and running simulations, but with advancements in AI, there are new questions about what lies ahead and the accuracy of these technologies.
At the NAPE Energy Business Conference, industry experts discussed the power and pitfalls of AI in the oil patch. One of the main challenges mentioned was ensuring data quality and gaining human trust in the technology. There are also concerns about AI potentially replacing jobs in the industry.
The benefits of AI in the oil patch were highlighted by Lisa Helper, an A&D geologist for Hilcorp Energy. She shared how ML algorithms can predict plunger failure, saving significant amounts of missed production. AI has also made tasks easier and faster for geologists, reducing the time it takes to complete tasks like gridding a map.
AI has the potential to analyze the subsurface and interpret large seismic volumes quickly, making it valuable for making quick decisions. Hilcorp Energy has already tested AI capabilities in the field, with impressive results. It took an employee six months to interpret faults, while the machine completed the task in just 3 hours.
Pushpesh Sharma, a senior product manager at AspenTech, emphasized how AI can help tackle complexity in data analysis. With the increasing complexity of workflows and datasets in the oil and gas industry, AI can be a valuable companion in improving productivity and efficiency.
However, the quality of data is crucial for successful implementation of AI technologies. Inconsistent or poor-quality data can lead to inaccurate results. To address this issue, the Open Standard Data Universe has been working on standardizing data formats in the industry.
While AI offers opportunities for optimization and efficiency, concerns about job security arise. Andrew Muñoz, COO of 4cast Inc., highlighted the importance of having enough data to train AI models and the need for ongoing maintenance. It is recognized that AI may replace certain tasks and roles but cannot fully replace a properly trained and experienced human workforce.
In conclusion, AI has the power to revolutionize the oil and gas industry, but there are challenges to overcome. Ensuring data quality, building trust, and addressing job security concerns are crucial in leveraging the full potential of AI in the oil patch. With the right approach, AI can improve efficiency, accuracy, and decision-making processes in this complex industry.
