

DATA
ENERGY


ACCURATE
PREDICTIONS

ENHANCED PERFORMANCE

NEW
INSIGHTS
Data science services include data science consulting, development, and support companies to run experiments on their geoscientific data in search of new business insights, improved performance, and accurate predictions.

DATA SCIENCE & ANALYTICS
We will map your analytics initiatives to quantifiable business opportunity with data-driven innovative solutions
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Data understanding and problem elaboration
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Data management with clean and efficient SQL
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Designing scalable data processing pipelines
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Building Python application for data visualization and analysis (custom build)
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Iterate models over and over to enhance predictions
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Deploying applications into cloud-based platforms (e.g., AWS), GUI production and dashboards
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Result-oriented data manipulation for analytical purposes
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Probability and statistical analysis, data distribution
MACHINE LEARNING
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Designing efficient and innovative machine learning solutions from pipelines to products
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Statistical modeling and hypothesis testing
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Building, training, and validating results from various machine learning algorithms
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Optimizing hyperparameters, model constructing with these parameters, evaluating model performances using different metrics
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Building deep learning networks using modern methods, such as PyTorch or TensorFlow
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Evaluating models iteratively to avoid overfitting and under-fitting

GeoData Science Process
Step 1: Define Prediction to Make
Define a hypothesis to test or parameter to make a prediction about (problem understanding)
Fault? Velocity? Lithology? Inversion?




...
Repeat
Step 2: Gather Data
Gather data with various sources and formats
(Data Lake: SQL)
Step 3: Clear Data
Handle missing values, statistical analysis
(feature engineering)
Step 4: Visualize Data & Explore
Plot numerical & categorical data
(matplotlib and seaborn in python)
Step 5: Build Predictive Models
Input-target error minimization
(Scikit-Learn, TensorFlow)
Step 6: Model evaluation & Production
Use evaluation metrics for 'goodness of fit'




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