Oil and Gas

Oil and Gas

Gain insights into the oil and gas industry with satellite imagery and machine learning.

In-Situ Oil and Gas Well Life Cycle Monitoring

Detect and monitor well development starting from early pad construction to a fully operational well. Kumi Analytics 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.

Hedge funds, commodity traders, fundamental traders

  • Get early trading signals for the oil markets and predict long term pricing trends.

Mineral Rights Traders

    • Make more strategic buying decisions with a deeper understanding of well development.

In-Situ High Consequence Area Monitoring

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.

Kumi Analytics 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 Companies

    • Assess and mitigate risk
    • Detect structure changes quickly at a reduced cost
    • Detect construction equipment before an accident occurs

  • Identify key structures nearby including multi-family dwellings, schools, hospitals, nursing homes, and places of worship

In-Situ Encroachment Monitoring

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.

Oil and Gas Companies

    • Assess and mitigate risk
    • Early identification of potential encroachments before they occur

In-Situ Methane Emission Detection

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.

Oil and Gas Companies

  • Mitigate pollution and save money by reducing fines for regulatory compliance
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