About This Item

Share This Item

The AAPG/Datapages Combined Publications Database

AAPG Special Volumes

Abstract

Click to view this article in PDF format.

Chapter from:
AAPG Memoir 71 : Reservoir Characterization-Recent Advances
Edited by Richard A. Schatzinger and John F. Jordan
Copyright 1999 by The American Association of Petroleum Geologists. All rights reserved.
Memoir 71, Chapter 16: Statistical Analysis of Surface Lineaments and Fractures for Characterizing Naturally Fractured Reservoirs, by Genliang Guo, Stephen A. George, and Rhonda P. Lindsey, Pages 221 - 250

Chapter 16


Statistical Analysis of Surface Lineaments and Fractures for Characterizing Naturally Fractured Reservoirs

 Genliang Guo
Stephen A. George
BDM Petroleum Technologies
Bartlesville, Oklahoma, U.S.A.

Rhonda P. Lindsey
DOE National Petroleum Technology Office
Tulsa, Oklahoma, U.S.A.


ABSTRACT

Thirty-six sets of surface lineaments and fractures mapped from satellite images and aerial photos from parts of the Mid-continent and Colorado Plateau regions were collected, digitized, and statistically analyzed to obtain the probability distribution functions of natural fractures for characterizing naturally fractured reservoirs. The orientations and lengths of the surface linear features were calculated using the digitized coordinates of the two end points of each individual linear feature. The spacing data of the surface linear features within an individual set were obtained using a new analytical sampling technique that involves overlapping a set of uniform imaginary scanlines orthogonally on top of an individual fracture set and calculating the distance between two adjacent intersection points along each scanline. Statistical analyses were then performed to find the best-fit probability distribution functions for the orientation, length, and spacing of each data set. Twenty-five hypothesized probability distribution functions were used to fit each data set. A chi-square goodness-of-fit value was considered the best-fit distribution.

Pay-Per-View Purchase Options

The article is available through a document delivery service. Explain these Purchase Options.

Watermarked PDF Document: $14
Open PDF Document: $24