The Use of Drone Geophysics to Locate and Map Legacy Oil and Gas Infrastructure

Wednesday, 12 June 2019: 13:10
Davie West Building, DW103 (Florida Atlantic University)
Richard w. Hammack, U.S Department of Energy, National Energy Technology Laboratory, Geological and Environmental Sciences, Pittsburgh, PA, United States and Garret Veloski, U.S. Dept. of Energy, National Energy Technology Laboratory, Geological and Environmental Sciences, Pittsburgh, United States
Abstract:
Because of concern that hydraulic fracturing fluids might migrate to the surface or into underground sources of drinking water via unplugged abandoned wells, the Pennsylvania DEP now requires oil and gas companies to locate wells within a 1000-ft-wide buffer around new wells to be hydraulically fractured. It is difficult for operators to fulfill this requirement because state well location records are incomplete for wells drilled prior to ~1950 and because wellheads are often concealed by dense vegetation. The National Energy Technology Laboratory (NETL) has been helping operators meet this requirement by developing rapid methods to surveil large areas for the presence of wells. Initially, helicopter magnetic surveys were used to detect the unique magnetic signature of vertical steel well casing. Although effective, this approach was expensive and did not detect wells with wooden casing (very old wells) or wells where the casing had been removed for reuse or salvage. Recently, the expense of airborne magnetic surveys was significantly decreased by the deployment of microfabricated atomic magnetometers (MFAM) on drone rotary aircraft.

However, the problem of locating wells with non-magnetic (e.g. wooden) casing or no casing remained. NETL and its industry partners are now evaluating the efficacy of using high-resolution drone Light Detection and Ranging (LiDAR) surveys to focus ground searches for abandoned wells. When flown during leaf-off conditions, this approach shows promise for locating well pads, pits, and flow lines based on subtle topographic expressions.