Abstract: A method can include deriving a cloud of microseismic events corresponding to a fracturing operation in an environment by spatially locating the microseismic events in the environment via a seismic velocity model; extracting a set of fracture planes from the microseismic cloud; assigning characteristics to the fracture planes; determining a second-rank fracture compliance tensor and a fourth-rank fracture compliance tensor based on the characteristics of the fracture planes; determining a change in elastic stiffness of the environment using the second-rank fracture compliance tensor and the fourth-rank compliance tensor; and updating the seismic velocity model based at least in part on the change in the elastic stiffness of the environment or determining permeability in the environment based at least in part on fracture plane locations, orientations and apertures. Various other apparatuses, systems, methods, etc., are also disclosed.

Abstract: A method can include deriving a cloud of microseismic events corresponding to a fracturing operation in an environment by spatially locating the microseismic events in the environment via a seismic velocity model; extracting a set of fracture planes from the microseismic cloud; assigning characteristics to the fracture planes; determining a second-rank fracture compliance tensor and a fourth-rank fracture compliance tensor based on the characteristics of the fracture planes; determining a change in elastic stiffness of the environment using the second-rank fracture compliance tensor and the fourth-rank compliance tensor; and updating the seismic velocity model based at least in part on the change in the elastic stiffness of the environment or determining permeability in the environment based at least in part on fracture plane locations, orientations and apertures. Various other apparatuses, systems, methods, etc., are also disclosed.

Abstract: Methods and apparatus that use microseismic event data, stress data, seismic data, and rock properties to predict the hydrocarbon production success of a well location are disclosed. An example method generates a hydrocarbon production function based on information associated with at least a first well location, obtains information associated with a second well location, and calculates the hydrocarbon production function using the information associated with the second well location to predict the hydrocarbon production of the second well location.

Abstract: Methods and apparatus that use microseismic event data, stress data, seismic data, and rock properties to predict the hydrocarbon production success of a well location are disclosed. An example method generates a hydrocarbon production function based on information associated with at least a first well location, obtains information associated with a second well location, and calculates the hydrocarbon production function using the information associated with the second well location to predict the hydrocarbon production of the second well location.

Abstract: Methods and apparatus that use microseismic event data, stress data, seismic data, and rock properties to predict the hydrocarbon production success of a well location are disclosed. An example method generates a hydrocarbon production function based on information associated with at least a first well location, obtains information associated with a second well location, and calculates the hydrocarbon production function using the information associated with the second well location to predict the hydrocarbon production of the second well location.

Abstract: Methods and apparatus that use microseismic event data, stress data, seismic data, and rock properties to predict the hydrocarbon production success of a well location are disclosed. An example method generates a hydrocarbon production function based on information associated with at least a first well location, obtains information associated with a second well location, and calculates the hydrocarbon production function using the information associated with the second well location to predict the hydrocarbon production of the second well location.

Abstract: A multivariate stochastic simulation application that involves the mapping of a primary variable from a combination for sparse primary data and more densely sampled secondary data. The method is applicable when the relationship between the simulated primary variable and one or more secondary variables is non-linear. The method employs a Bayesian updating rule to build a local posterior distribution for the primary variable at each simulated location. The posterior distribution is the product of a Gaussian kernel function obtained by simple kriging of the primary variable and a secondary probability function obtained directly from a scatter diagram between primary and secondary variables.