A prevalent consensus on the next technological breakthrough involves the emergence of AI and machine learning for commerce use. For the petroleum and the energy industry by, this leap has a profound influence on the status quo of operations and protocols. If the vast amount of data influx from the industry could potentially be streamlined and optimally processed, the trends and potential solutions ascertained by machine learning programs would extraordinarily impact operational growth and capacity. For decades this concept has been pursued, but has been economically or environmentally impractical to operate for individual corporations. The viability has recently changed granted the advent of cloud technology introduces by tech giants.
The oil and gas industry deals with a huge influx of valuable data from field operations and process facilities. Drilling, completions and productions data is very useful in increasing efficiency and output by making decisions which depend on precedence and history, as a chunk of petroleum engineering deals with history matching and conjecture given the inconceivably numerous variables in each situation.
The advent of machine learning and AI has revolutionised the way in which data can be manipulated to achieve unparalleled efficiency. AI and machine learning use the seemingly endless arrays of individually meaningless data to recognise distinct patters, and ascertain causal relationships which are otherwise impossible to interpret. The programs make use of the patterns and trends to intervene complete operations with a greater efficiency and with minimal human intervention. The data influx is continuously transformed into very valuable operational changes made by the programs, a few of the applications include automated monitoring and adjustment of gaseous emissions from productions and drilling sites, intervening and optimising production conditions in the well bore, interpreting the reservoir characteristics to predict future performance.
Earlier, the operational cost constraint on corporations rendered such projects to be non viable. The third party cloud operations introduced by Amazon, Google and Microsoft offer the appropriate solution. Under the new Cloud operation protocol, the data would be shared with the third party such as Google or Microsoft for assessment. The limitless capability of Cloud platforms is further facilitated by the emerging concept of Internet of Things(IoTs), which refers to the application of networks and internet for devices which do not possess an operating software. Devices such as valves, transformers, pumps, and compressors which can be operated directly through the cloud platform. Recognising the potential for this technology Exxon and Chevron have partnered with Microsoft Azure, a pioneering platform for AI. Total signed an agreement with Google Cloud late last year. Schlumberger has also long been involved with Google Cloud to optimise reservoir field services.
AI capabilities in the petroleum industries will reduce the dependency of human intervention—which naturally comes with its risk factor. The future role of petroleum engineers would conceivably shift to a macro super-visionary role rather than a micromanaging job.
コメント