Integrated rock classification in carbonate formations based on elastic and petrophysical properties estimated from conventional well logs Conference Paper uri icon

abstract

  • Copyright 2014, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. A reliable rock classification in carbonate reservoirs should take into account petrophysical, compositional, and elastic properties of the formation. However depth-by-depth assessment of these properties is challenging, as the result of complex pore geometry and significant heterogeneity caused by diagenesis. Common rock classification methods in carbonate formations are typically based on core measurements and require an extensive core database, whereas core data are usually not available at all desired depths. Furthermore, elastic properties, which control fracture propagation and the conductivity of fracture under closure stress, are often not taken into account in conventional rock classification techniques. In this paper, we apply an integrated rock classification technique based on both depositional and diagenesis effects to significantly enhance (a) assessment of petrophysical properties, (b) selection of candidates for fracture treatment, and (c) production in carbonate reservoirs. We jointly apply conductive and elastic effective medium theories to estimate depth-by-depth volumetric concentration of interparticle (e.g., interconnected pore space) and intraparticle (e.g., vugs) pores, as well as elastic bulk and shear moduli, in the formation. This process takes into account the impact of shape and volumetric concentrations of rock components on electrical conductivity and elastic properties. We document a successful application of the introduced technique in the Upper Leonardian carbonate interval of the Veterans field, in West Texas. The identified rock types were verified using thin-sections, core samples, and high-resolution borehole image logs, where available. We estimated elastic moduli as well as interparticle porosity with average relative errors of approximately 8% and 14% compared to the core measurements, respectively. Furthermore, the well-log-based estimates of permeability and water saturation were improved by approximately 50% and 20%, respectively.

published proceedings

  • SPWLA 55th Annual Logging Symposium 2014

author list (cited authors)

  • Saneifar, M., Conte, R., Chen, C., Heidari, Z., & Pope, M. C

complete list of authors

  • Saneifar, M||Conte, R||Chen, C||Heidari, Z||Pope, MC

publication date

  • January 2014