Fracability evaluation
Shale resource plays are associated with low permeability, and hence hydraulic fracturing is required for their stimulation and production. The effective propagation of complex fractures is dependent on a rock’s ability to fail in a brittle manner. For this reason, pockets in organic shale formations that exhibit higher brittleness are selected for reservoir completion by way of fracturing. While there are different ways (geomechanical, mineralogical and elastic parameters) of defining brittleness, there is no universally accepted indicator of brittleness. However, geophysicists seem to be avid followers of Rickman et al. (2008)’s, brittleness index (mentioned below), proposed a decade ago.
Crossplot of Young’s modulus versus Poisson’s ratio for Barnett shale.
Brittle zones are identified based on the criterion of low Poisson’s ratio and high Young’s modulus. This criterion works well if a negative correlation exits between these two parameters as noticed for Barnett shale shown below. Therefore, the generalization of this criteria for different unconventional plays could be dangerous.
“Correlation of high Young’s modulus with brittleness gets criticism from geomechanics / engineering domain as highlighted below”
Three different scenarios of ductile and brittle failure as well as the stress-strain curves for four different triaxial tests carried out under different confinement pressures have been depicted here. It is noticed that brittle failure may occur at low as well as high values of Young’s modulus. Higher confinement leads to higher Young’s modulus but ductile failure.
A relationship between brittleness index and confining stress defined geomechanically indicates that the best fracability behavior is associated with low confining stress. However, the brittleness index defined by Rickman shows the opposite trend. Therefore, it can be stated that the Rickman et al. (2008)’s approach ignores the confining stress that the rocks are always under, and hence ignores the true mechanism of hydraulic fracturing.
The mechanism of hydraulic fracturing: Hydraulic fracturing of rocks entails the initiation of fractures and their propagation as depicted below. To initiate a fracture, priority should be given to a material which absorbs less energy before it gets fractured. Once the fracture is initiated, the stress state within the rock gets disturbed due to stress concentration at the crack tip. A rock can withstand fracture tip stresses up to a critical value, which is referred to as the critical stress intensity factor; this ability of a rock to resist fracturing and propagation of pre-existing fractures is known as fracture toughness. Rocks with low fracture toughness promote fracture propagation. Thus, the amount of energy that a formation consumes in the fracture initiation process as well as its fracture toughness must be considered in identifying the favorable zones to be fractured.
Considering the above definition, we introduce a new attribute called hydraulic fracturing coefficient (HFC) which involves strain energy density (SED) and fracture toughness (FT) in its estimation.
Validation of HFC as a measure of fracability
Using experimental data: Using experimental data collected from different regions comprising uniaxial compression test, scanning electron microscope (SEM) and X-ray diffraction methods were analyzed Hu et al. (2015) to obtain the mechanical properties, texture and crack characteristics of rocks. The test results were given in terms of Young’s modulus, Poisson’s ratio, confining pressure, compressive strength, peak strain and residual strain for data samples from Haynesville shale, Eagle Ford shale, Barnett shale and Longmaxi shale. Considering compressive strength as a measure of fracability, brittleness index as well as HFC are crossplotted with compressive strength as illustrated below.
HFC accounts the impact of strength on the fracability analysis appropriately
HFC: Application on well-log data from Delaware Basin
(Adapted from Sharma et al., 2019)
Different clusters of data points corresponding to different combinations have been enclosed and back projected on the well-log curves. While the data points corresponding to Bone Spring formation are showing a combination of high and low FT and SED, respectively, the data points from Lower Wolfcamp and Barnett formations exhibit an opposite combination of these two attributes. However, both these combinations are not preferable for hydraulic fracturing as they lead to the low values of HFC.
Higher values of HFC are more appealing, and come from an optimal combination of FT and SED. Such a combination is observed for an interval within the Wolfcamp (green ellipse), which is essentially a limey shale as seen in the mud-log strip. An important conclusion from the above exercise is that, a small proportion of limestone within the shale offers a suitable condition for fracture initiation and propagation.
HFC: Application on well-log data from Appalachian Basin
Crossplot between SED and FT for well data over an interval from the Utica to Trenton limestone geologic markers, color coded with (a) Vclay (b) Vcarbonate (c) Vquartz (d) total porosity. Notice, data points corresponding to the Utica formation exhibit optimal combination (< 50% clay, < 40% carbonate) of different mineral constituents along with the high porosity. (Adapted from Sharma et al., 2019)
HFC: Application on seismic data (Delaware Basin)
An arbitrary line passing through different wells extracted from the (a) HFC volume (b) Litho-facies volume. The fracability variation noticed laterally within the Bone Spring is supported by the facies volume as high content of carbonate suggests low fracability on the eastern side. Similarly, the variation of fracability noticed in the individual intervals (ellipses and polygon) can be supported again with the facies volume and the concept of confining pressure that increases with time/depth. (Adapted from Sharma et al., 2019)
References
Holt, R. M., E. Fjaer, O. M. Nes, and H. T. Alassi, 2011, A shaly look at brittleness, 45th US Rock Mechanics/Geomechanics Symposium, ARMA, 11-366, San Francisco, CA, USA.
Hu, Yu., M. E. G. Perdomo, K. Wu, Z. Chen, K. Zhang, D. Ji and H. Zhong, 2015, A novel model of brittleness index for shale gas reservoirs: confining pressure effect, SPE-176886, Society of Petroleum Engineers.
Lutz, S. J., S. Hickman, N. Davatzes, E. Zemach, P. Drakos, A.R. Tait, 2010, Rock mechanical testing and petrologic analysis in support of well stimulation activities at the desert peak geothermal field, Nevada, in: Proc. 35th Workshop on Geothermal Reservoir Engineering, Stanford Univ., CA, USA.
Rickman, R., M. J. Mullen, J. E. Petre, W. V. Grieser, and D. Kundert, 2008, A practical use of shale petrophysics for stimulation design optimization: All shale plays are not clones of the Barnett shale: SPE Annual Technical Conference and Exhibition, SPE, 115258.
Sharma, R. K., S. Chopra and L. R. Lines, 2019, Replacing conventional brittleness indices determination with new attributes employing true hydrofracturing mechanism, submitted for publication in Interpretation, T1081-T1095.
Sharma, R. K., S. Chopra, S., and L. R. Lines, 2019, Replacing conventional brittleness indices determination with new attributes employing true hydrofracturing mechanism, presented at 2019 SEG Convention, held at San Antonio, in September. (O)