Integration of surface seismic, microseismic, and production logs for shale gas characterization: Methodology and field application

Abstract

Technologies such as horizontal drilling and multistage hydraulic fracturing are central to ensuring the viability of shale oil and gas resource development by maximizing contact with the most productive reservoir volumes. However, characterization efforts based on the use of well logs and cores, although very informative, may be associated with substantial uncertainty in interwell volumes. Consequently, this work is centered around the development of a predictive tool based on surface seismic data analysis to rapidly demarcate the most prolific reservoir volumes, to identify zones more amenable to hydraulic fracturing, and to provide a methodology to locate productive infill wells for further development. Specifically, we demonstrate that surface seismic attributes such as λρ/μρ crossplots can successfully be employed to quantitatively grade reservoir rocks in unconventional plays. We also investigate the role of seismically inverted Poisson's ratio as a fracability discriminator and Young's modulus as an indicator of total organic carbon richness and porosity. The proposed predictive tool for sweet spot identification relies on classifying reservoir volumes on the basis of their amenability to fracturing and reservoir quality. The classification scheme is applied to a field case study from the Lower Barnett Shale and we validate these results using production logs recorded in four horizontal wells and microseismic data acquired while fracturing these wells. The integration of seismic data, production logs, and microseismic data underscores the value of shale reservoir characterization with a diverse suite of measurements to determine optimal well locations and to locate hydraulic fracture treatments. A key advantage of the methodology developed here is the ease of regional-scale characterization that can easily be generalized to other shale plays.

Identification of brittle/ductile areas in unconventional reservoirs using seismic and microseismic data: Application to the Barnett Shale

“…Although hydraulically induced fractures can propagate through ductile and brittle rocks, the goal of the proppant is to better preserves induced fractures in more brittle rocks. Alzate (2012) combines production logs and microseismic data with simultaneous seismic inversion attributes to analyze completion effectiveness along four horizontal wells in the Barnett Shale. He concludes that the hydraulically generated fractures preferentially grow toward the more brittle rock, generating a difference in gas production.…”

Estimation of the Shale Oil/Gas Potential of a Paleocene–Eocene Succession: A Case Study from the Meyal Area, Potwar Basin, Pakistan

“…The brittle and rich TOC zones are also marked from the correlation of elastic parameters in cross-plots . Alzate (2012) and Alzate and Devegowda (2013) observed that variation in Young's modulus (E) is a consequence of TOC. Based on their concepts, three zones can be identified within the Patala Track 1 (DT4P -P-wave Sonic log, DT4S -S-wave Sonic Log); Track 2 (VSH -Volume of shale); Track 3 (VP -P-wave velocity, VS -S-wave velocity estimated by using the relationship of Han et al, 1986); Track 4 (IP -P-wave acoustic impedance, IS -S-wave acoustic impedance); Track 5 (PR -Poisson's ratio, E -Young's modulus); Track 6 (TNPH -Neutron porosity, PHIT -Average porosity); Track 7 (B -Brittleness Index); and Track 8 (K -Permeability).…”

Shale Oil Play Exploration Delineation Using Rock Mechanics Template and Seismic Inversion Data. Vaca Muerta Formation, Neuquén Basin, Argentina

“…These parameters are known as "dynamic". The first step on our workflow is mainly calibration of the static-to-dynamic relationship in order to then apply such as relationship to the dynamic well log data Once this correction is applied, the integration of the parameters is done by using a rock mechanics template (RMT) modified after Alzate (2012), where a series of regions had been discriminated in terms of mechanical behaviour and TOC content. After this analysis is done using well log data, this region has been applied in a 3D fashion onto a seismic cube.…”