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Modelling earthquake risk of gas fields


Using qualitative modelling, the risk of earthquakes due to gas extraction can be determined more clearly. “This is done by using three dimensional modelling software to calculate and simulate the forces and movements around geological faults deep under the ground,” says Frans Mulders who, on 3 December, will defend his PhD thesis at TU Delft. “Currently, the KNMI determines the probability of earthquakes primarily through statistical data,” says Mulders. “It is important to complement that data with knowledge of the geological structure underground.” Mulder conducted his research in cooperation with TNO-NITG, NAM, Shell, KNMI and State Supervision of Mines.

In recent months, three light earthquakes hit the province of Groningen. Geologists agree that the quakes are related to gas extraction. It is possible to use historical statistical data of these kind events to make a prediction for the future. “That is what the KNMI (national research and information centre for climate, climatic change and seismology) is currently doing,” says Mulders. “Valuable data, but combining this with knowledge of underground the geological structure is worth recommendation. This is currently being worked on at TNO-NITG in cooperation with KNMI.”

Mulders used three dimensional (3D) simulations to research activity deep under the ground. He has integrated so-called Mobilised Shear Capacity (MSC) parameters into his models. This parameter provides a numerical value for the instability of certain layers and the faults they contain. Mulders: “Such a parameter, linked to other data, forms a basis for the calculation of the probability of earthquakes near gas fields.” According to Mulder, earthquakes will continue to happen every now and then in Groningen. “As long as gas is extracted, there will be movement in the ground.”

The numerical models that Mulders has developed are representative for the underground of the Northern Netherlands, but due to their generic character they are also representative for other oil and gas fields in similar conditions. “Here the weakness of the models also shows,” says Mulders, “While you can simulate many situations with the 3D models, you need a lot of data on the geological structure of the area to produce good estimations. This data is often lacking.” The combination of statistics, 3D modelling and geological information needs further research.

Maarten van der Sanden | alfa
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