Abstract: A multivariate analysis may be used to correlate seismic attributes for a subterranean formation with petrophysical properties of the subterranean formation and/or microseismic data associated with treating, creating, and/or extending a fracture network of the subterranean formation.

Abstract: A multivariate analysis may be used to correlate seismic attributes for a subterranean formation with petrophysical properties of the subterranean formation and/or microseismic data associated with treating, creating, and/or extending a fracture network of the subterranean formation.

Abstract: A computing device can use a support vector machine to categorize well data as being associated with a noise event or a microseismic event. For example, the computing device can determine well data based on sensor signals from a sensor in a wellbore. The computing device can then use the support vector machine to categorize the well data as being associated with a noise event or a microseismic event.

Abstract: Microseismic-event data can be corrected (e.g., to reduce or eliminate bias). For example, a first distribution of microseismic events that occurred in a first area of a subterranean formation can be determined. The first distribution can be used as a reference distribution. A second distribution of microseismic events that occurred in a second area of the subterranean formation can also be determined. The second area of the subterranean formation can be farther from an observation well than the first area. The second distribution can be corrected by including, in the second distribution, microseismic events that have characteristics tailored for reducing a difference between the second distribution and the first distribution.