Pays International Ltd:

Free 30-Day Pilot Study: AI/ML Geoscience Services
Test out the Artificial Intelligence and Machine Learning techniques before any serious investment for your company



Welcome to Pays International’s revolutionary AI/ML Geoscience Services! We are excited to offer you a free 30-day pilot study, where you can experience the power of our advanced machine learning technologies, seamlessly combined with traditional techniques, to unlock the true potential of your seismically derived data. Our primary objective is to provide you with a comprehensive analysis of your geoscience data, encompassing Classification, inversion, and fault analysis, to empower your exploration and decision-making processes.

* we charge an administration fee

Scope of Work:
Experience the depth and value of our pilot study, as we tailor the analysis to achieve your specific objectives:

a. Data Acquisition and Preparation:
In this phase, we work closely with you to acquire the necessary volumes of reflectivity data, horizon data, and well data. We ensure the data is accurately prepared and organized, setting the stage for a robust analysis.

b. Classification Analysis:
During the pilot study, our expert team will showcase the seamless blend of traditional deterministic tools and advanced AI/ML techniques to perform a comprehensive Classification of your seismic data. Witness how our AI-driven algorithms and deep neural network architectures uncover intricate geological features, faulting, lithofacies, and potential hydrocarbon reservoirs, delivering invaluable insights.

– Traditional Techniques: Observe the application of deterministic methods, such as seismic waveform inversion and attribute analysis, to identify lithology, porosity, and fluid content. This foundational step builds a solid foundation for subsequent AI/ML analyses.

– Advanced AI/ML Techniques: Experience the power of our state-of-the-art machine learning models, including deep neural networks, support vector machines, and clustering algorithms, which process vast amounts of data and identify complex patterns, significantly enhancing the accuracy of lithofacies and hydrocarbon identification.

c. Inversion Analysis:
Witness the seamless integration of traditional and AI/ML techniques during the pilot study, as we enhance the resolution and quality of your seismic data, providing a clearer view of subsurface structures and properties. By incorporating well data and low-frequency information, we estimate accurate wavelets and compute acoustic impedance, enabling you to make more informed reservoir-related decisions.

– Frequency Compensated Inversion (FCI): Observe traditional FCI methods in action as we extract detailed information about the subsurface, including acoustic impedance, density, and shear impedance. This process enhances the seismic data and improves the understanding of subsurface characteristics.

– AI/ML-Driven FCI: Experience how our AI/ML algorithms refine FCI results by incorporating geological constraints and supplementary data, overcoming limitations and increasing the accuracy and reliability of the inversion process.

d. Fault Analysis:
During the pilot study, gain essential insights from our comprehensive analysis, which involves a blend of traditional fault detection methods and cutting-edge AI/ML techniques, including convolutional neural networks. Experience firsthand how we expertly identify faults and characterize their attributes, providing you with invaluable data for interpretation and decision-making processes.

– Traditional Fault Detection: Observe established techniques, such as coherence analysis and curvature attribute analysis, in action, as we identify faults in the seismic data. This foundational step aids in fault localization and mapping.

– AI/ML-Driven Fault Analysis: Witness our application of convolutional neural networks (CNN), conducting a detailed and automated fault detection process, accurately capturing complex fault patterns and characteristics. This advanced technique improves fault characterization, leading to more precise geological interpretations.

AI/ML Fault Analysis

AI/ML Seismic Inversion

AI/ML Classification

Reservoir Characterisation using Artificial Intelligence and Machine Learning 30-Day Pilot Study

Intelligent Drill Placement

Prior to Quantitative Interpretation, deciding on oil well placements required great imagination and insight, yet still yielded a poor success rate. At Pays International we employ a more surgical approach, increasing the success and profitability of an oil field through powerful seismic data analysis techniques.

Through these techniques we are able to give your petroleum engineers and geologists the best possible information on where the next well should be drilled.

What we do

Structural Analysis

The latest in fault analysis, curvature analysis and RGB blending techniques. Structural analysis provides an accurate insight into the structure in and around your reservoir.

Seismic Inversion

Porosity, fluid prediction and brittleness index are some of the most crucial factors in reservoir characterisation. Seismic inversion calculates these factors from your data.

Machine Learning Classification

From your well data, estimates can be made about the importance of certain attributes in terms of likelihood of finding oil. Our machine learning algorithm learns from these data and predicts where to drill the next well.