What are the best practices for characterizing rock properties for drilling engineering purposes?

1 Rock property definitions

Rock properties, such as density, porosity, permeability, compressibility, Young's modulus, Poisson's ratio, unconfined compressive strength, tensile strength, and shear strength, are physical and mechanical characteristics of the rock that affect its behavior under stress and fluid flow. These properties are essential for drilling engineering because they impact hydrostatic pressure, buoyancy of the drill string, fluid storage and flow capacity, pore pressure and wellbore stability, stiffness and rigidity of the rock, contraction or expansion of the rock, resistance to crushing and fracturing, resistance to cracking and splitting, and resistance to sliding and tearing.

2 Rock property measurement

Rock properties can be assessed through various methods, depending on the availability, accuracy, and cost of the data. Laboratory testing involves taking core samples from the wellbore and subjecting them to tests in a controlled environment, providing accurate and reliable data; however, it is time-consuming and expensive. Logging involves running tools or sensors along the wellbore to measure physical or electrical properties of the rock, offering continuous and real-time data; however, it can be affected by borehole conditions and interpretation models. Seismic involves generating and recording sound waves that propagate through rock layers, providing large-scale and high-resolution data; yet, it is complex and costly. Lastly, empirical correlations involve using mathematical equations or charts that relate rock properties to other parameters that are easier to measure, such as depth or porosity; while this method can provide quick and simple data, it is based on assumptions and regional variations.

3 Rock property analysis

Rock property analysis is the process of using measured data to evaluate rock strength and drillability, and to optimize drilling operations. This process includes data quality control, which involves checking validity, consistency, and completeness of the data, and correcting or discarding any outliers, errors, or missing values. Data integration combines and compares data from different sources and methods, while data interpretation applies physical or mathematical models to the data. Data visualization presents the data in graphical or numerical formats, such as histograms, crossplots, maps, or tables. Finally, data utilization uses the data to design and adjust drilling fluids, bits, and parameters; as well as to monitor and control drilling performance and safety.

4 Rock property challenges

Rock property characterization is not a straightforward or simple task, as it faces many challenges and uncertainties. Heterogeneity, anisotropy, nonlinearity, and uncertainty are all common issues that complicate the process. Heterogeneity can make it difficult to obtain representative and consistent data, while anisotropy can make it hard to compare data from different orientations. Nonlinearity can make it hard to extrapolate data from different stress or fluid regimes, while uncertainty can be caused by measurement errors, interpretation errors, or inherent variability. All of these factors can lead to difficulty in predicting the rock behavior under different stress and fluid conditions, accounting for directional effects on the rock response, capturing complex and dynamic rock behavior, and quantifying and reducing uncertainty.

5 Rock property best practices

Rock property characterization is a critical and challenging task for drilling engineering, but it can be improved and enhanced by following some best practices. Planning ahead involves setting objectives, scope, and budget, as well as selecting the appropriate methods, tools, and models. Collaborating with stakeholders such as geologists, petrophysicists, reservoir engineers, and drilling engineers is essential for sharing and integrating data and knowledge. Validation of data and models is also necessary by using independent or alternative methods, sources, or standards. Updating the data and models with new or additional information is important, as well as learning from the rock property characterization to apply to future projects.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?