Easily connect your well log data
Connect to your choice of data sources (On-premises files, cloud, SQL, OSDU, Techlog, …), integrate and prepare your well log data and get lithofacies classification per depth.Explore !
In the energy industry, identifying the most advantageous well locations is often an elusive task. In practice, determining optimal well sites can be especially challenging given the intricate nature of reservoir and depletion scenarios. Understanding the characteristics of facies types present is crucial for accurately estimating physical properties like porosity and permeability, identifying, and simulating reservoirs, designing optimal acidizing jobs, and even for well completion and drilling. By precisely classifying the facies, we can gain a better understanding of the depositional environment that the wellbore has penetrated.
Core samples of reservoir rocks provide petrophysicists and geologists with the most reliable source of lithofacies information. However, as these samples are often limited in availability, finding alternative approaches to do without or with more limited cores is critical.
Leveraging the wealth of data captured from past cores gives the opportunity to extrapolate rock lithofacies from cored wells to uncored wells by comparing wireline log measurements of petrophysical properties like density, porosity and resistivity, and others. By easily using historical data and computing required metrics, SLB Facies Classification analytical template gives petrophysicists and geologists the possibility to quickly classify lithofacies based on well log data. This lithofacies classification will be the starting point to get a good reservoir model closer to the reality to reduce uncertainties and risks for the exploration and production.