Petrophysics and Image Analysis

Basics of log evaluation and introduction to measurements on rock. Practical laboratory work on porosity, permeability, capillarity, parameter determination of rock, principles of acoustic, electric, electro-magnetic and nuclear measurements in boreholes, identification of water and hydrocarbons, quantification of reservoir properties. 

Lectures and exercises: 
Introduction to the identification, measurement and use of physical rock parameters. Rock mineral content and rock textures, of mainly sedimentary rocks, are related to properties like density, conductivity, magnetics, (natural/induced) radiation, acoustics and rock mechanics.

In relation to the reconstruction of a synthetic mineral content, methods to derive porosity, permeability and capillarity are discussed and calculated in practicals. The practical work consists of five ways to measure permeability/porosity and to determine rock mechanical properties by using a combined acoustic/stress experiment.

Details:
1. Laboratory measurement: Darcy-flow and porosity.
A. Experiments at the Geoscience and Engineering Laboratory. This work includes measurements on solid and porous cores. Measured are: Bulk volume and bulk weight and the related matrix volume and matrix density; Calculation of the porosity on the two porous samples, with a dry method and the wet/dry method; Calculation of the gas-permeability of the two porous samples; Estimation of the measurement errors and calculation of the accuracy of the measurements. 
B. Combined acoustic and rock mechanical measurements. Uni-axial stress is put on a solid core. Different types of acoustic waves are used to measure travel time through the undamaged and fractured rock specimen. Elastic moduli are calculated from both measurement types.

2. Empirical relations. 
A. Carman-Kozeny permeability. Based on spatial distributions of a porous rock texture, porosities and permeabilities are calculated by using statistical spatial characteristics, i.e. grain size distributions, derived volumes and specific surfaces. 
B. Quantification of grain sizes and grain-size distributions, by using rock surfaces and images.
In this exercise the students get familiar with the concept of empirical relations. How are grain-size distribution, porosity, permeability and capillarity connected to each other? 

Well log measurement principles and data processing and interpretation through petrophysical models. Indirect measurements to estimate physical parameters are outlined for the most important well logs. Petrophysical models for resistivity, density and seismic velocity are introduced and related to the log measurements. Exercise on synthetic and real logs are carried out to apply petrophysical model to data integration and quantitative log interpretation.

Petrophysics:

1.     Fluid conductivity and effect of temperature, salinity and pressure. Archie’s Law and its modification for shaly sand formations

2.     Solid and fluid mechanical properties. Willye and Gassmann models for monomineral materials, fluid substitution. Voight-Reuss average for multimineral media. Effect of porosity and mineralogy on those properties

Logs:

1.     General concepts about logs: investigation depth and resolution. Mud invasion, caliper logs

2.     Lithology logs: Self potential and Gamma ray, measurement principles, corrections and data quantitative interpretation. Shale volume estimation

3.     Resistivity logs, laterolog, focalized tools and induction log measurements and data correction. Water saturation estimate.

4.     Neutron and Density logs: measurement principles and data corrections. Estimate of porosity through Neutron-Density cross plot.

5.     Sonic logs: measurements principles, porosity estimation.

6.     Image logs: measurements principles and bedding azimuth and dipping estimation.

7.     Log lithological interpretation and fluid recognition from integration of different log measurements. Case study presentation.

Synthetic log exercise: autonomous work to retrieve the petrophysical properties from a synthetic log dataset. The quantitative analysis of the different logs allows rock and fluid properties to be retrieved and porosity models to be identified.

Field log interpretation exercise: unsupervised work on real log data to carry out lithology identification, fluid identification, estimation of shale volume, porosity, water saturation.