A Practical Petrophysical Approach for Brittleness Prediction from Porosity and Sonic Logging in Shale Reservoirs

Abstract

Brittleness has been used as one of the important descriptors for the characterization of unconventional shale reservoirs. The degree of brittleness in shale reservoirs is determined upon the basis of its mineralogical composition, which can be obtained from mineralogical logging tools (such as ECS™, FLeX™, GEM™, Litho Scanner™), or XRD tests in the laboratory. Generally, measurements of mineralogical brittleness are obtained from physical sources and lead to relatively reliable interpretation results. However, mineralogical logging is expensive and not commonly available in the shale play. Alternatively, brittleness can also be calculated from dynamic Young's modulus and Poisson's ratio, but the absence of shear slowness in some wells restricts its wide application. Internal friction angle based brittleness can give similar interpretation results as the preceding two methods, but its accuracy depends highly on the quality of correlations. It is observed that the curves of the three different brittlenesses demonstrate similar shapes. Therefore, we have attempted to build correlations between mineralogical brittleness and porosity or sonic compressional slowness for typical shale plays (Woodford, Barnett, and Eagle Ford shale), and have proven their validity with the data obtained from wells not included in the development of correlations. Applications of these findings include: (1) enabling the possibility of evaluating brittleness in plays lacking mineralogical and shear sonic loggings, thus reducing the quantity of laboratory testing, (2) inspiring operators to develop in-house correlations of brittleness for shale gas plays, and (3) investigating similar correlations in emerging unconventional oil plays, such as Granite Wash.

A Review of Brittleness Index Correlations for Unconventional Tight and Ultra-Tight Reservoirs

“…The LBI on the other hand can be directly derived from wireline logging using the Neutron Porosity (NPHI) or the compressional slowness. Empirical equations yield to the BI [13]. The EBI can be subdivided into static and dynamic properties.…”

Rock anisotropy and brittleness from laboratory ultrasonic measurements in the service of hydraulic fracturing

“…The grains of the proppant could be pressed into the surface of the fracture, so as the effective width of the fracture would be decreased and therefore fracture conductivity may decrease. In the light of above it can be stated that tested samples of Mancos shale would be hard to fracturing.In the case of the measured Sample ID BRIT Jarvie et al, 2007 BRIT Wang & Gale, 2009, modified BRIT Jin et al, 2014a, 2014b brittleness indexes (mineral and geomechanical) should be used complementary. It should be mentioned as well, that the extrapolation of laboratory tests to the field encounters some problems.…”

Brittleness index prediction in shale gas reservoirs based on efficient network models

“…Lai et al (2015) performed a statistical regression analysis to find relationships between brittleness and conventional well logs, and the ratio of gamma rays to the photoelectric absorption cross section index showed a good correlation with mineralogical brittleness. Jin et al (2014b) attempted to build correlations between mineralogical brittleness and compressional slowness for four U.S. shale plays. The results were more promising for predicted brittleness than only using neutron porosity.…”