Detect and monitor well development starting from early pad construction to a fully operational well. Insituit utilizes feature recognition of equipment to identify the stage of well creation and serves as an early signal for both oil and gas production rates. Additional signals include timeseries analysis of roads and tailing ponds construction in established oil fields.
High consequence area (HCA) monitoring is a critical safety requirement for oil and gas utilities transmission pipelines. Annual monitoring is required and the timely identification of habitable structures and public meeting places improves compliance measures and helps to prioritize pipeline integrity operations.
Insituit utilizes high resolution imagery with change detection to identify new and revised structures, business listings data, and other data sets as part of the risk mitigation strategy.
Oil and gas transmission pipeline encroachments are of high risk for utility operators. High cadence, high resolution imagery analysis of change with machine learning techniques is now possible providing regular insights to encroachment activities such as irrigation construction, adjacent civil construction programs, housing developments, etc. Additionally, machine learning methods provide insights as to the occurrence if encroachment is occurring geospatially enabling you to focus your monitoring activities where they need to be.
Satellite sensors are capable of detection of methane emissions. By combining sensor data with machine learning algorithms, near real-time analyses of plumes and emissions is now possible — enabling the mitigation of emissions that result in environmental regulation breaches and corporate governance requirements.