Abstract: Techniques and systems to provide increases in accuracy of property determination of a formation. The techniques include receiving initial well log data, generating augmented well log data including the initial well log data and modeled well log data based on the initial well log data, modifying the augmented well log data to generate a training dataset, training a probabilistic classifier utilizing the training dataset, calculating a probability volume for each lithofluid class of a set of predetermined lithofluid classes utilizing the probabilistic classifier, outputting the probability volume for each lithofluid class of the set of predetermined lithofluid classes as a respective probability of an occurrence of a type of lithofluid class in a reservoir, calculating a posterior probability based on the probability volume for a first lithofluid class of the set of predetermined lithofluid classes, and outputting the posterior probability as a probability of a property of the reservoir.

Abstract: A method includes receiving, via a processor, a first seismic dataset generated using a first type of survey system. The method further includes receiving, via the processor, a second seismic dataset generated using a second type of survey system. The method additionally includes determining a frequency band in which to combine the first seismic dataset with the second seismic dataset to generate a combined dataset and generating a seismic image based upon the combined dataset, wherein the seismic image represents hydrocarbons in a subsurface region of the Earth or subsurface drilling hazards.

Abstract: Techniques to allow for increases in the accuracy of the determination of properties of a formation (e.g., a formation's fluid content, porosity, density, etc.) or seismic velocity, shear wave information, etc. are disclosed herein. The techniques include generating initial input data comprising based at least in part on initial seismic data, modeling the initial input data to generate synthetic seismic data based on different combinations of the initial input data, iteratively updating a value of each particle of a set of particles utilizing the synthetic seismic data to generate a final set of particles and outputting the final set of particles as a target distribution.