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Title: Natural and Induced Fracture Diagnostics from 4-D VSP Low Permeability Gas Reservoirs

Technical Report ·
DOI:https://doi.org/10.2172/963893· OSTI ID:963893

Tight gas sand reservoirs generally contain thick gas-charged intervals that often have low porosity and very low permeability. Natural and induced fractures provide the only means of production. The objective of this work is to locate and characterize natural and induced fractures from analysis of scattered waves recorded on 4-D (time lapse) VSP data in order to optimize well placement and well spacing in these gas reservoirs. Using model data simulating the scattering of seismic energy from hydraulic fractures, we first show that it is possible to characterize the quality of fracturing based upon the amount of scattering. In addition, the picked arrival times of recorded microseismic events provide the velocity moveout for isolating the scattered energy on the 4-D VSP data. This concept is applied to a field dataset from the Jonah Field in Wyoming to characterize the quality of the induced hydraulic fractures. The time lapse (4D) VSP data from this field are imaged using a migration algorithm that utilizes shot travel time tables derived from the first breaks of the 3D VSPs and receiver travel time tables based on the microseismic arrival times and a regional velocity model. Four azimuthally varying shot tables are derived from picks of the first breaks of over 200 VSP records. We create images of the fracture planes through two of the hydraulically fractured wells in the field. The scattered energy shows correlation with the locations of the microseismic events. In addition, the azimuthal scattering is different from the azimuthal reflectivity of the reservoir, giving us more confidence that we have separated the scattered signal from simple formation reflectivity. Variation of the scattered energy along the image planes suggests variability in the quality of the fractures in three distinct zones.

Research Organization:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
FC26-06NT42956
OSTI ID:
963893
Country of Publication:
United States
Language:
English