Rock Strength from Core and Logs, Where We Stand and Ways to Go
- Abbas Khaksar (Helix RDS Ltd.) | Philip Geoffrey Taylor (Helix RDS Ltd.) | Zhi Fang (Helix RDS Ltd.) | Toby John Kayes (Helix RDS Ltd.) | Abraham Salazar (Helix RDS Ltd.) | Khalil Rahman (Helix RDS Ltd.)
- Document ID
- Society of Petroleum Engineers
- EUROPEC/EAGE Conference and Exhibition, 8-11 June, Amsterdam, The Netherlands
- Publication Date
- Document Type
- Conference Paper
- 2009. Society of Petroleum Engineers
- 3.2.5 Produced Sand / Solids Management and Control, 1.6 Drilling Operations, 1.6.9 Coring, Fishing, 4.3.4 Scale, 5.1 Reservoir Characterisation, 5.1.5 Geologic Modeling, 1.2.3 Rock properties, 5.6.9 Production Forecasting, 5.1.4 Petrology, 5.6.2 Core Analysis, 1.2.2 Geomechanics, 2.2.2 Perforating, 1.12.2 Logging While Drilling, 1.14 Casing and Cementing, 5.5.2 Core Analysis, 2.5.1 Fracture design and containment, 5.6.1 Open hole/cased hole log analysis, 4.1.2 Separation and Treating, 5.1.3 Sedimentology, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 2.4.3 Sand/Solids Control, 5.3.4 Integration of geomechanics in models, 4.1.5 Processing Equipment, 1.8 Formation Damage, 5.1.2 Faults and Fracture Characterisation
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Knowledge of accurate rock strength is essential for in situ stress estimation, wellbore stability analysis, sand production prediction and other geomechanical applications. Reliable quantitative data on rock strength can only be obtained from cores. However, cores are limited, discontinuous and often biased. Consequently, rock strength evaluation is primarily based on log strength indicators, calibrated where possible against limited core measured values. There are a number of published log-core strength correlations that can be used for rock strength modelling. These empirical relationships are developed for specific rock type, age, depth range and field. Their general applications, therefore, need to be critically assessed on a case by case basis. This paper briefly: (i) outlines the best practice for obtaining quality rock strength data from core tests; (ii) presents common empirical rock strength equations for sedimentary rocks and (iii) discusses ways of improving rock strength estimates.
While some equations such as porosity-based or sonic log-based rock strength models work reasonably well, rock strength variations within individual rock properties show considerable scatter, indicating that most of the empirical models are not sufficiently generic to fit all rocks in the database. Like any other physical rock properties, the variation in rock strength in a given sedimentary rock is controlled by mineralogy, sedimentology and micro-structure of the rock and simple log-derived rock strength models need further modification and classification incorporating these geological characteristics.
This paper has shown that when sufficient core rock strength data exists, applications of computing techniques, such as fuzzy logic and cluster pattern recognition, coupled with sedimentary facies analysis and diagenetic classification can improve strength estimation. Semi-continuous impact energy logs using portable non-destructive testing tools can be correlated with petrophysical logs to generate mechanical facies and improved sampling for conventional rock testing.
Rock mechanical properties are essential for accurate in situ stress analysis and geomechanical evaluations including wellbore stability analysis, sand production prediction and management, hydraulic fracturing design, fault stability and reactivation analysis and other geomechanical applications. The rock mechanical parameters typically required to populate a geomechanical model based on the linear Mohr-Coulomb failure criterion are: Unconfined Compressive Strength (UCS or C0), Friction angle (q) or Coefficient of internal friction, m (where m = tanq), as well as Thick Wall or hollow Cylinder strength (TWC) which may be needed for sanding evaluation and calibration. These properties are commonly known as rock strength parameters. Other essential rock mechanical properties are elastic moduli. The two most common required elastic constants are; Poisson's ratio (n) and Young's modulus (E) from which other elastic moduli such as shear and bulk moduli can be derived. While rock elastic moduli can be derived from well logs (bulk density, both compressional and shear sonic logs), reliable quantitative data on rock strength parameters can only be derived at specific depths from laboratory tests on core samples. Laboratory measurements of elastic moduli on core samples subjected to the in-situ stress condition are also needed to calibrate log-derived (dynamic) elastic moduli to static values measured on cores.
Laboratory-based rock strength values are typically determined through triaxial tests on cylindrical samples that are obtained from cores at depths of interest. Continuous profiles of rock strength against depth can be estimated using well logs and empirical core-log relationships. Ideally, log-derived strengths should be calibrated by direct laboratory measured values to ensure that the results are reasonable for the rocks under analysis. However, in most cases the core strength databases are limited, discontinuous and often biased toward stronger intervals. Quality core plugs of non-reservoir formations (for example, mudstones and shales), where most of hole instability problems occur, are rarely available for testing. In practice, many geomechanical problems are often addressed in the absence of core samples for laboratory testing. Consequently, rock strength evaluation is primarily based on log strength indicators, calibrated where possible against limited core measurements.
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