PowerLog

Harness machine learning tools and technology by connecting your preferred Python distribution to PowerLog and perform in-house advanced processing and interpretation to save your company time and money. Interactive clustering, synthetics, and data analysis workflows read and write directly to a PowerLog project database.

Machine learning in PowerLog enables a clearer reservoir understanding and faster, more efficient data analysis so you can predict curves based on existing log data, correlate core analysis to log data, model complex porosity and permeability relationships, and quickly edit logs for data conditioning with automated tools.

Build accurate rock physics models from log data and petrophysical interpretation results with easy-to-use, collaborative Rock Physics Module (RPM). RPM bridges the gap between PowerLog and other Jason geophysical software applications. This user-friendly module is integrated with PowerLog so you can iterate on your petrophysical parameters using rock physics models and improve your petrophysics interpretation for a better understanding of the subsurface.

RPM enables a fundamental modeling approach — a petrophysical rock model is used to derive rock structure information and effective elastic rock properties from fluid and mineral parameters. Users can easily analyze fluid-substitution studies and invasion corrections once a rock model is constructed. The rock model also enables prediction of elastic curves for lithology parameters that are not present in the wells.

In complex environments, deterministic methods are insufficient. StatMin is a stochastic analysis tool for determining volumes of fluids and minerals and statistical methods for petrophysical analysis of difficult formations. StatMin generates meaningful interpretations in complex lithologies that enable solid decisions for optimum reservoir completions.

StatMin obtains valuable outputs such as porosity, water saturation and quartz, which are key petrophysical parameters needed to make critical completion decisions. It also solves balanced, over determined and underdetermined models. Under determined models are more common where insufficient log data is available to compute all the needed minerals in one pass. StatMin provides users multiple methods to solve this challenge and allows for more accurate analysis of these complex reservoirs.

PowerLog FaciesID is a user-friendly electrofacies classification tool that allows for the reconstruction of input curves as block curves and performs a quality check of results during the process.

Geoscientists use the PowerLog Capillary Pressure tool to evaluate well logs and cores from multiple wells and zones to model saturation versus height above free water level (FWL). The resulting analytical expressions relate either connate water saturation to height above FWL (forward modeling), or height above FWL to connate water saturation (reverse modeling). Findings from one well can be applied to other wells in the area, making the process efficient and consistent.

The innovative machine learning workflow with automated depth matching along with automated curve patch editing uses automated detection of spikes and anomalous data to improve the quality of interpretations and facies analysis while greatly reducing data preparation time ‒  for one well, or hundreds of wells.