[CCoE Notice] THESIS DEFENSE ANNOUNCEMENT_ARYAB MAZUMDAR8_

[UH Cullen College of Engineering]

THESIS DEFENSE ANNOUNCEMENT_ARYAB MAZUMDAR8_16.docx<cid:830FE4437E9F9DC27B53B59780AEF3ECA8B9C218 at 1>



Master’s Thesis Defense

Aryab Mazumdar
Petroleum Engineering

Topic: Developing predictive models for strength properties in conventional reservoirs

Date: Thursday, August 19, 2021
Location: Technology Bridge (Formerly ERP) Building 9, Room 140
Time: 3:00 pm – 5:00 pm

Committee Chair: Dr. Lori Hathon

Committee Members: Dr. Michael Myers, Dr. George Wong
Abstract
We obtain MWD data on almost every well and it represents a first - hand look at the geomechanical properties of the penetrated section. Details of the variability in mineralogy and geochemistry of the penetrated section are often related to the rock strength. In highly heterogeneous unconventional reservoirs trends in geochemical data have been used as proxies for TOC and the “brittleness” of the formations.  We propose to test the same technique in a highly heterogeneous (thin bedded) conventional reservoir.

All of the data is acquired from a vertical wellbore with full diameter core. Core plugs representing the variability of the section were obtained. Suites of geochemical tests (ECS log, XRF – handheld and powder) were also performed on the core. The handheld XRF and the powder XRF were in good agreement. The elemental concentration data were plotted against strength estimates obtained from a core scratch test, and UCS estimated from depth based and time based MWD data, and from dual energy CT imaging to look for relationships between bulk chemistry and rock strength.  In particular, the influence of clay mineral content (using Al as a proxy) was of interest. The estimated strength properties of the thin bedded sand/shale sequence were not simply related to bulk chemistry, including proxies for clay minerals and typical cement phases carbonate, nor was there in good agreement among the various estimates of UCS In addition to geochemical proxies, estimated rock strength was also regressed against porosity, particle size, and acoustic properties, among others.  Ongoing analyses include comparing UCS estimated from the core scratch test and MWD data to core plug measurements of rock strength, and sample characterization (porosity, net:gross, point count data etc.) from CT and thin section imaging and image analysis.  Future work will include data analytics models to predict UCS from these data.
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