Georg Zangl

State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

Artificial intelligence (AI) has been used for more than two decades as a development tool for solutions in several areas of the EP (b) approximately 50% of respondents declared they were somehow engaged in applying workflow automation, automatic process control, rule-based case reasoning, data mining, proxy models, and virtual environments; (c) production is the area most impacted by the applications of AI technologies; (d) the perceived level of available literature and public knowledge of AI technologies is generally low; and (e) although availability of information is generally low, it is not perceived equally among different roles. This work aims to be a guide for personnel responsible for production and asset management on how AI-based applications can add more value and improve their decision making. The results of the survey offer a guideline on which tools to consider for each particular oil and gas challenge. It also illustrates how AI techniques will play an important role in future developments of IT solutions in the E&P industry. Introduction While there is hardly a rigorous definition of the term artificial intelligence (AI) that is unequivocally accepted, the tools of AI and its intended uses have been well studied for decades and many applications have appeared. Loosely speaking, AI is the capability of machines (usually in the form of computer hardware and software) to mimic or exceed human intelligence in everyday engineering and scientific tasks associated with perceiving, reasoning, and acting. Since human intelligence is multifaceted, so is AI, comprising goals that range from knowledge representation and reasoning, to learning, to visual perception and language understanding (Winston 1992). AI techniques have been present in the E&P industry for many years. A quick literature search reveals application of AI in SPE scientific and engineering papers as early as in the 1970s. There are numerous references about the applications of neural networks, fuzzy logic, genetic algorithms, expert systems, and other artificial techniques in the resolution of problems in diverse areas, such as reservoir simulation, production optimization, process control, and fault detection and diagnosis, among many others. AI is an area of great interest in the E&P industry, mainly in applications related to production control and optimization, proxy model simulation, and virtual sensing. The most popular techniques are artificial neural networks, fuzzy logic, and genetic algorithms, with interesting developments in hybrid and nontraditional techniques. There has been recent increase in such AI-based commercial applications for production management. While the full impact of such applications is still being realized, there are already solutions in the market with a positive impact in the E&P industry.