Periodic Reporting for period 2 - VirtualSeis (Virtual Seismology: monitoring the Earth's subsurface with underground virtual earthquakes and virtual seismometers)
Reporting period: 2019-03-01 to 2020-08-31
In this project novel methodology is developed for creating virtual seismic sources (earthquakes or seismic vibrators) and virtual seismometers anywhere in the subsurface, from seismic measurements (active and passive) at the earth’s surface. This is called Virtual Seismology (VS). VS accurately mimics the responses to actual earthquakes that would be recorded by actual buried seismometers, including all multiple scattering effects.
In particular VS will be developed for:
WP1. Investigating induced-earthquake problems.
WP1a. High-density multi-component seismic acquisition methodology will be developed (Distributed Acoustic Sensing: DAS), using the latest technology of controllable seismic vibrators and seismic sensing with fibre-optic cables, and it will be applied in an actual induced-earthquake sensitive area in Groningen.
WP1b. The data of WP1a will be used to create virtual sources and receivers in the subsurface to characterize induced earthquakes, quantify the ground motion of actual and possible future earthquakes, and monitor the geomechanical state of the area.
WP2. Imaging and monitoring subsurface fluid flow. Highly repeatable VS methodology will be developed for time-lapse 3D reflection data to monitor fluid-flow processes in the subsurface with excellent spatial and temporal resolution.
WP1b. From active and passive seismic measurements at the earth’s surface, VS aims at creating virtual seismic sources and/or receivers in the subsurface and the responses between them. At the start of the project, VS worked well on idealized 1D and 2D synthetic data. We further developed VS for forecasting and monitoring the complex seismic wave field and associated ground motion caused by induced seismicity in realistic scenarios.
Since real sources in the subsurface may have complex radiation properties (e.g. double-couple sources) and extended spatial and temporal distributions (e.g. rupturing faults), we generalized VS to create virtual double-couple sources and virtual rupturing faults at any desired position in the subsurface. The wave fields generated by these virtual sources can be monitored by virtual receivers in the subsurface, all the way from the virtual source to the surface. We evaluated the method on existing seismic reflection data from the Vøring Basin (Norway) and were able to forecast the entire response to virtual point sources and virtual rupturing faults in a data-driven way. We made significant progress in extending the methodology to account for elastodynamic wave propagation and scattering and for 3D applications.
WP2. Virtual seismic sources and receivers in the subsurface obtained by VS from reflection data at the surface can be used for imaging of structures and monitoring of fluid flow, fully accounting for internal multiple scattering. We extensively investigated how VS performs for realistic acquisition configurations, and developed a method to account for imperfect sampling. To improve the efficiency of time-lapse methods, we developed a target replacement method, accounting for all orders of multiples. A significant efficiency gain (by a factor 10 to 100) is further obtained by creating virtual plane-wave sources instead of point sources.
To become less dependent on a background velocity model, we developed methods that project the virtual sources and receivers to the surface. The latter approach provides multiple-free reflection data at the surface which can be further processed with standard primary imaging schemes.
We are investigating how the integration of VS with full waveform inversion and the use of multiply scattered waves can help to improve the determination of target parameters and the resolution of time-lapse changes in a target zone. We have successfully applied VS imaging to seismic field data from the Santos Basin, Brasil, both in 2D and in 3D settings.
WP1b. The VS methodology which creates responses between virtual sources and receivers in the subsurface is based on the multidimensional Marchenko method. The application we are developing in WP1b for forecasting and monitoring the seismic wave field of induced seismic sources is entirely novel. In the next period the VS methodology of WP1b will be applied to the active and passive data that will be acquired with the DAS network in WP1a. This combination of WP1a and WP1b is a novel method for forecasting and monitoring the seismic wave field of induced seismic sources.
WP2: The VS methodology for imaging and monitoring is also based on the multidimensional Marchenko method. The advantage of this method is that it eliminates internal multiple scattering and thus largely improves seismic imaging. During the reporting period we introduced several novel research lines to improve VS for imaging and monitoring in realistic situations (accounting for imperfect spatial sampling, 3D situations, elastodynamic effects) and in a very efficient way. In the next period we will integrate VS methodology with multi-scale subsurface flow modelling, aiming to link time-lapse seismic images with subsurface flow processes.