Summary
Skills
Overview
Work History
Education
Timeline
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Blaine Murphy

Blaine Murphy

Data Scientist
Houston,TX

Summary

Proactive and enthusiastic professional with 6 years of experience analyzing data and creating predictive models to make business decisions in the oil and gas industry. Aiming to leverage my skills and experience to create value as a Data Scientist at your company.

Skills

  • Python
  • SQL
  • Statistical Analysis
  • Data Visualization
  • Machine Learning
  • Regression
  • Classification
  • Unsupervised Learning
  • Deep Learning
  • Signal Processing
  • Time Series Analysis

Overview

7
7
years of professional experience

Work History

Data Science Fellow

Springboard
Houston, TX
04.2021 - 11.2021
  • Extensive 600+ hour data science course, working 1:1 with an industry mentor, utilizing Python, SQL, hypothesis testing, data wrangling, data visualization, feature engineering, machine learning, and deep learning
  • Predicting West Nile Virus Outbreaks, binary classification using daily weather data to predict where WNV outbreaks will occur in Chicago
  • Revenue prediction using Google Analytics, regression prediction of user revenue for the Google retail store

Geophysicist

Noble Energy
Houston, Texas
08.2014 - 07.2020
  • Performed rock physics modeling and AVO analysis to predict seismic response for various fluid and lithology cases
  • Created and applied core calibrated petrophysical models to accurately estimate reservoir properties for two business development opportunities
  • Identified bias in previous petrophysical model, created new model using first principals with improved accuracy to core calibration
  • Modeled missing well log data using TensorFlow to evaluate fringe acreage
  • Built supervised classification model to delineate rock types for reservoir simulation
  • Operations petrophysicist for pilot and production lateral, providing real-time quantitative interpretation and drilling guidance. Well was drilled ~70% in pay sands and came on line producing ~18,000 bbls/day, doubling total field production
  • Work culminated in leasing 40,000+ acres with stacked pay potential
  • Produced predictive maps from multivariate linear models using geological, petrophysical, and engineering data
  • Using Python, normalized log curves and unsupervised clustering of log data from 50,000+ wells to delineate different rock types
  • Quantitatively characterized organic rock richness and maturity using linear modeling in Python, applied to 20,000+ wells
  • Created new method of aggregating log data using Python to compare different reservoirs and emphasize horizontal development and stacked pay potential
  • Wrote Python script to analyze horizontal well placement relative to stratigraphy calculated from surfaces, vertical wells and deviation surveys.
  • Quantified effect of stress field and fault orientation on horizontal well production by using Python to integrate seismic attributes, subsurface stress data, and production data
  • Built and applied neural network models to predict rock properties from seismic data

Geophysicist

Deep Imaging Technologies
Houston, TX
05.2013 - 08.2013
  • Updated finite element code to model electric field generated from large electric dipole in 3D
  • Created Python functions for processing and analyzing raw field data

Geophysicist

EMGS
Houston, TX
05.2012 - 08.2012
  • Responsible for processing 3D ocean bottom controlled-source electromagnetic data and performed inversions for identification of resistive anomalies

Education

Master of Science - Geophysics

Texas A&M University
College Station, TX

Bachelor of Science - Physics

Texas A&M University
College Station, TX

Timeline

Data Science Fellow

Springboard
04.2021 - 11.2021

Geophysicist

Noble Energy
08.2014 - 07.2020

Geophysicist

Deep Imaging Technologies
05.2013 - 08.2013

Geophysicist

EMGS
05.2012 - 08.2012

Master of Science - Geophysics

Texas A&M University

Bachelor of Science - Physics

Texas A&M University

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