Luc Sandjivy, Seisquare  

Abstract Title: Quantifying Uncertainty in Depth Imaging: Issues and Challenges

Acceptance by processing geophysicists to discuss the reliability of the subsurface and O&G reservoir images they produce is a major breakthrough for the industry. Quantifying Uncertainty in Depth imaging is obviously related to Quantifying Confidence in SubSurface and Reservoir models supporting E&P decisions. It is thus a two-step process, first about quantifying the quality of a seismic image, that is its resolution and sharpness, second about quantifying the reliability of the seismic data for imaging the geology and hydrodynamic of the subsurface at the reservoir scale. Quantifying Uncertainty in Depth imaging means quantifying the unknown difference between a seismic image and the actual subsurface, that is the imaging error. Only probabilistic models (geostatistics) allow for defining this error as a specific kind of estimation error and use it as a cost function to be minimized when modelling reservoirs. Further and deeper integration of Kriging algorithms in geophysical processing and imaging processes will certainly lead to significant optimization of the parametrization of the geophysical processes and to quantified improvement of E&P project performance. 

Konstantin Osypov, Aramco Americas Research Center 

Abstract Title: Quantifying Uncertainty in Depth Imaging: From Rays to Waves

Ray-Tomography based uncertainty analysis has been studied over a decade with multiple examples demonstrating the business value. However, quantifying uncertainty with wave-based methods is more challenging. I’ll show examples of uncertainty analysis using ML-based FWI proxy inverting VSP data.  

Christopher Lee Slind, PETRONAS

Abstract Title: Embedding Uncertainty from Velocity Model Building into the Exploration Workflow 

A discussion on taking what we learn from uncertainties in model building in seismic imaging and propagating them for further use by our exploration teams. There will be additional discussions about ideas to capture uncertainty from the current mix of imaging techniques.

John T. Etgen, BP

Abstract Title: How do we begin to have a proper conversation about uncertainty  

We could see the question of how to estimate and communicate the uncertainty of the positioning of our images as a purely mathematical question. However, I think it might be best to first understand some of the human weaknesses in talking about probabilities and uncertainties and then use a more empirical approach to illustrate how these uncertainties are manifest in practical situations.