Artificial Intelligence for Automating Seismic Horizon Picking

Abstract

Fully-automated seismic horizon picking dramatically shortens the time between acquiring seismic data and picking drilling targets. Oil and gas exploration companies worldwide spend millions of tedious man-hours picking horizons on seismic data to produce inventories of drilling targets. Freeing up that time to better incorporate the geologic and geophysical properties within mapped structures guarantees more drilling success. Artificial intelligence is frequently mentioned in today’s news: self-driving cars, vehicle identification, robot vacuums, fingerprint identification, facial recognition and Alexa are just a few examples. Why not seismic data interpretation? Here, it is proven that automated seismic horizon picking is possible. From a two-column text file of time-amplitude pairs my algorithm produces a reflection-time-ordered text file of all continuous series of connected pixel coordinates easily-read by mapping software. These connected pixels are plotted separately on the input seismic test line’s peaks and troughs. More than 10,000 connected segments were written in less than a minute of computer time, saving many hours of manual labour. This time-saving extrapolated to 3D seismic surveys will reduce the time it takes to find drilling targets by months.