Ivan Lim is currently a research geophysicist and data translator at Chevron Technical Center with five years of industry experience. He holds an Engineering degree in Electronics (2013) from Multimedia University, Malaysia. He also has an MSc (2015) and PhD (2019) in Geophysics from Imperial College London and Colorado School of Mines. His main research interest is in distributed acoustic sensing (DAS) and data science.

Abstract:

Hydraulic fracturing induces a network of fractures to promote the flow of oil and gas in tight shale reservoirs. In this paper, we discuss the detection of fracture hits during stimulation to avoid reaching an observing well. Our aim is to devise an early warning system for cases where fracture interference may adversely affect production. We propose the use of image-based algorithms such as template matching and convolutional neural network (CNN) on low-frequency signals of distributed acoustic sensing (DAS) data to detect precursor events leading to a fracture hit.