Many operators commit to reducing their operation's carbon dioxide (CO2 emissions. According to McKinsey & Company (2020)(1) , well drilling and extraction processes contribute 8% of the Scope 1 emissions in the oil and gas industry. Rig site activities generate one-third of the overall emissions footprint for the well construction process. A well construction process consists of hundreds of activities and tasks ranging from well spud to rig release. Along the way, many different types of equipment are used. To minimize emissions, we need to analyze how the power is used and how it can be saved throughout the well construction process. Selecting lower-carbon energy sources can significantly reduce Scope 1 emissions, but the transition process takes time. The operator and contractor must continually improve their operation's efficiency to reduce emissions.

The emissions footprint model was developed based on CO2 emissions data and power consumption statistics for land rigs. During well planning, the engineer strives to formulate a drilling program considering the anticipated time, cost, and overall emissions objectives. Emissions volumes should be calculated based on the equipment used in each activity. The engineer compares the technologies proposed for the drilling program to determine the optimum equipment solution with the lowest overall environmental impact. The ability to forecast expected emissions for planned wells helps the engineer make technology selections for each drilling plan. With validated models, it's possible to calculate the CO2 released based on the measured drilling parameters and work to reduce it. For sustainability purposes, the engineer must consider the total emissions created by the entire process as an additional performance indicator.

In this paper we describe the integration of emissions footprint modeling into the overall well-planning workflow. We developed the model by measuring actual emissions and power usage of different rig equipment during different drilling activities. This was done by using a cloud-based well-construction planning solution. The workflow was embedded into the overall well design, enabling the engineer to visualize each project's anticipated time, cost, and emission. Energy consumption was correlated using the provided drilling parameters. Therefore, the emission can be successfully predicted for different well-construction scenarios, drilling technology, and related parameters. This new workflow enables the engineer to plan with sustainability objectives and determine the best overall drilling program for each project.

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