A working method for estimating dynamic shear velocity in the montney formation

摘要

class="kwd-title">Abbreviations: DTP, sonic log – compressional slowness, DTS, sonic log – shear slowness, NNE, neural network estimation, GR, gamma ray log, RCW, reservoir characterization workflow, RHOB, bulk density, SSTVD, subsea true vertical depth in meters, Vp, compressional sonic velocity, Vs, shear sonic velocity, VsANN, shear velocity log estimated using artificial neural network techniques, Vs DOL, shear velocity log estimated using Greenberg-Castagna [1] Dolomite lithology constants, Vs SH, shear velocity log estimated using Greenberg-Castagna [1] Shale lithology constants, Vs SST, shear velocity log estimated using Greenberg-Castagna [1] Sandstone lithology constants, Vs LST, shear velocity log estimated using Greenberg-Castagna [1] Limestone lithology constants, Vs MDRK, shear velocity log estimated using Castagna et al. [5] Mudrock lithology constants, Vs MJ Clavier, shear velocity log estimated using Marion & Jizba [11] method with Clavier et al. [12] fractional clay volume correction, Vs MJ Larionov, shear velocity log estimated using Marion & Jizba [11] method with Larionov [13] fractional clay volume correction, Vs MJ Stieber, shear velocity log estimated using Marion & Jizba [11] method with Stieber [14] fractional clay volume correction, VsRegress, shear velocity log estimated from the bivariate analysis of dipole sonic Vp and Vs logs, Vsh, Clavier, Clavier et al. [12] fractional clay volume correction, Vsh, Larionov, Larionov [13] fractional clay volume correction, Vsh, Stieber, Stieber [14] fractional clay volume correction class="kwd-title">Method name: Dynamic shear velocity estimation from compressional velocity logs in the Montney Formation class="kwd-title">Keywords: Log analysis, Velocity, Correlation, Tight reservoir, Siltstone, Shale class="head no_bottom_margin" id="abs0010title">AbstractIn this paper, we present a customized method for estimating sonic shear velocity (Vs) from compressional velocity (Vp) logs in the Montney Formation, in wells lacking dipole sonic data. Following a multi-scenario analysis that comprised of assessing empirical Vs estimation relations [including lithology, porosity (Ø), and volume of clay (Vsh)-based Vs estimation techniques], bivariate statistics, and machine learning, we found that the Greenberg & Castagna (1992) shale lithology constants yield Vs log estimates that best match the measured Montney Formation Vs in our study area, with a regional correlation coefficient of 0.8. We have therefore customized the Vs estimation method in our study to use the Greenberg & Castagna (1992) shale lithology constants. Our working method: class="first-line-outdent" id="lis0005">

• Improves the efficacy of Vs log estimation from Vp logs in the study area

• Demonstrates the importance of calibrating empirical relations for Vs estimation to a specific formation, and

• Provides a more accurate complementary Vs log dataset for subsequent regional reservoir characterization studies