Russian and Iranian Scientists Create AI Algorithm to Detect Water in Oil Reservoirs
The breakthrough promises to transform oil exploration and extraction by offering unprecedented accuracy and reducing costs and delays in field development.
Researchers from Russia’s Perm Polytechnic University and Iran’s Persian Gulf University have developed an artificial intelligence–based technology capable of evaluating oil reserves in reservoirs with remarkable precision. The new approach could reshape hydrocarbon exploration and production in both countries and beyond, according to the university’s press office.
The importance of this innovation for the oil industry is hard to overstate. By improving reserve estimates, companies can better plan production and investments. The system saves time and money by replacing expensive, slow laboratory studies with instant results. It also optimizes extraction: by mapping the distribution of oil and water, engineers can choose the most efficient development methods—crucial for aging and complex wells.
The central challenge in reservoir evaluation is determining how much oil and how much water a formation contains, as water can make up to 70 percent of the rock’s volume. Traditional analysis of core samples is costly, time-consuming, and often inaccurate. The new algorithm eliminates the need for lengthy lab work.
According to Dmitry Martyushev, professor of oil and gas extraction engineering at Perm Polytechnic, the machine-learning algorithm processes just nine parameters routinely collected from wells—such as depth, porosity, and rock resistance. Based on this data, the AI can forecast water content with up to 99.5 percent accuracy.
