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Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, for improved geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

In depth imaging, depth calibration using well-tie updated velocity is generally applied to poststack data. This is the most correct type of depth calibration as it positions structures in their proper places.

One of the main challenges in seismic imaging, especially of land data, is building the near surface velocity model, as it is normally characterized by very low velocity values with different types of local anomalies. Resolving the near surface velocity model using only refraction data is insufficient, as it does not provide the required lateral resolution. Using only reflection data is equally insufficient, as it does not provide the required vertical resolution.

Geothermal energy is a key resource for providing clean, reliable and sustainable energy. Induced seismicity events, with magnitudes large enough to be felt by local communities and impact surface infrastructures, are an undesirable potential result of geothermal operations, and significantly impact social acceptance. Mitigating adverse effects is of upmost importance if one wishes to increase the number of safe, sustainable geothermal projects.

Aspen Economic Evaluation provides an integrated estimation solution for effective management of projects across the entire lifecycle.

The ability to define an accurate interval velocity model resulting in a reliable image of the subsurface is a key challenge in prestack depth imaging. The delineation of an accurate interval velocity model is at the heart of every depth imaging process, so it is of vital importance to have all the input needed to ensure the velocity model is accurate, high resolution and geologically realistic.

Field development planning using reservoir models is a key step in the field development process. Numerical optimization of specific field development strategies is often used to aid planning, and Bayesian Optimization is a popular optimization method that has been applied in the past.

Elastic inversion from common reflection angle migration (CRAM) gathers can accurately capture lithology-driven lateral variations in reservoir properties, particularly in a strongly deformed and faulted geologic environment.

Predicting the permeability of fractured reservoirs is valuable for both reservoir assessment and drilling planning. Characterization of such systems requires advanced amplitude analysis, mainly based on seismic imaging results of the recorded wavefield.