CCS is the process of capturing carbon dioxide in geological formations deep underground and storing it to avoid its release into the atmosphere. The process is vital to combat global climate change, and it can be used to store a variety of different types of carbon.

The Carbon Capture Petrophysics by CCS can be reused as a fuel or stored in geological structures for future use. It can also be used to power industry processes or create new materials such as carbon fiber.

However, before CO2 can be injected into a rock formation, the process needs to be properly understood. This includes a lifecycle analysis from screening studies through to development, monitoring and abandonment - many elements of which are comparable to conventional hydrocarbon exploration and production workflows.

A Carbon Capture Petrophysics approach can help ensure that carbon capture and storage is properly planned and executed. It will also allow for a more efficient injection strategy to minimize the cost and environmental impacts of the project.

This Carbon Capture Petrophysics approach can be used in both oil and gas and non-hydrocarbon industries, such as nuclear waste storage and renewable energy. It will help to reduce risk, increase operational efficiency and lower costs for businesses across these sectors.

It will also help to prevent the risk of a leak or contamination. This can be achieved by establishing seal capacity, plumbing, trap/fault integrity and subsurface geomechanical stresses.

The Carbon Capture Petrophysics approach can also be used to identify specific sedimentary facies based on well log data. This can be useful for determining the lithology of a reservoir, as well as identifying effective porosity ranges.

Using machine learning, this Carbon Capture Petrophysics approach can be applied to seismic data to predict sedimentary facies from a 3D volume. The application of bi-variate statistics is used to compare the neurons of a machine learning algorithm with the Net Reservoir condition, and if there is a statistically significant relationship between the neuron responses and the corresponding sedimentary facies, then the resulting predictions will be able to match the underlying geology, enabling a more precise assessment of potential reservoirs in the area.

A Carbon Capture Petrophysics assessment of a reservoir can provide insight into its quality and potential to deliver commercial value. This can be invaluable for investors seeking to gain a competitive edge over their competition in the upstream oil and gas market, especially in the case of Mergers Acquisitions or Private Equity investments.

This Carbon Capture Petrophysics assessment can be applied in both oil and gas and non-hydrocarbon technologies, such as geothermal energy. It will help to determine the lithology of a reservoir, and if there is a correlation between its quality and its potential to deliver commercial value.

It can also be used to assess the potential for a geothermal field to capture and store carbon dioxide, as well as to detect the presence of carbon dioxide in a geological structure. The application of machine learning can be used to identify specific sedimentary facies, as well as identifying effective porosity levels.