Imran Chaudhary

AI-Enhanced Geoscience & Drilling Analytics - Shell, GOM, Oman & Brazil

Norphlet Reservoir - GOM
• Data Engineering & Automation: Extended the “pybasin” Python library to ingest and structure AOI, JSON, and shapefile data into BASIN objects and SQL tables within Databricks, enabling large‐scale geoscience processing.
• Geochemical & Reservoir Analysis: Applied PCA on XRF data for elemental clustering and formation classification; generated ternary plots to assess Smackover source rock heterogeneity (siliciclastic vs. carbonate); published results via AGOL web mapping for spatial analysis.
• AI-Driven Visualization & Decision Support: Developed an interactive Plotly-Dash Geochem App for real-time well correlation, formation comparison, and geochemical visualization, fully integrated with Databricks workflows.
• ML Modeling & Predictive Drilling Analytics: Built ML models for drilling performance optimization and conducted generative AI experiments to simulate drilling KPIs and forecast NPT (Nonproductive Time) for APPO WEST exploration wells in the Norphlet/Smackover unconventional reservoir.

Reservoir Analysis, Oman-Block 10-11 (Haushi Group)
• Data Engineering & Visualization: Performed exploratory data analysis on structured and unstructured datasets (storing outputs as BASIN objects via pickle files) and created interactive Plotly-Dash dashboards for interval-specific logs and reservoir property visualization.
• Reservoir Characterization & Real-Time Drilling Analytics: Evaluated sand presence, seal pair integrity, and reservoir quality using log properties; developed Dash-based tools for formation comparisons and automated trip analysis (via Shell Vantage web scraping) integrated into Databricks for live NPT monitoring.
• Facies Classification via ML: Deployed Gradient Boosting models for log-based facies classification, enhancing formation evaluation and reservoir characterization; validated models using accuracy scores, confusion matrices, and recall metrics.

Data-Driven Reservoir Characterization & Predictive Modeling for Miocene-GOM
• Data Engineering & Analytics: Constructed a comprehensive Miocene-GOM database using BDNA extraction and historical lookbacks; performed multivariate success factor analysis and ML modeling to support portfolio evaluation and prospect screening for GOM Block Lease assessments.
• Predictive Modeling & Drilling Parameter Estimation: Developed petrophysical workflows for Reservoir Seal Pair (RSP) calculations, computed porosity, permeability, and reservoir properties across wells; built ML models for drilling parameter estimation and wellbore stability prediction, integrating results into Plotly Dash and Spotfire dashboards.
• Generative AI & Data Governance: Tested generative AI models for ROP and Bit wear/tear forecasting to predict upcoming NPT; led data governance, compliance strategies, and cloud-based workflows using GitHub Enterprise Managed User (EMU) for Shell.

AWS & Databricks-Powered AI Generative Modeling-Pressure Analysis (VES) - SriGas23, Brazil
• Data Engineering & AWS Integration: Extracted and structured pressure, formation tops, and well data from LAS, Excel, TXT, and images; created top aliases and organized datasets in AWS for scalable, cloud-based analytics.
• AI-Driven Pressure & Risk Analysis: Assessed seal retention failure and Base of Salt/Breach risks; developed Databricks dashboards to visualize failure risks, potential kicks, and losses; applied Python-based vertical effective stress (VES) modeling to compute predictive pore pressure for high-risk wells.
• 3D Subsurface Mapping & Well Tie Analysis: Conducted Python-based well tie analysis and generated mistie plots to identify seismic-to-well mismatches; created 3D subsurface maps for volumetric reservoir interpretation.

• Real-Time Drilling Analysis & Cloud Integration: Aggregated and structured drilling/tripping event logs using SQL; managed ETL workflows and cloud resources across AWS and Databricks. Developed interactive dashboards in Plotly Dash for real-time drilling efficiency improvement.

• Wellbore Stability Analysis& Pore Pressure Modeling: Delivered real-time PPFG and WBS modeling for Mad Dog Phase 2, Thunder Horse, and Atlantis projects (BP GOM). Integrated Formation Integrity Test (FIT) & Leak-Off Test (LOT), and DFIT for optimized casing design and rig release.

• Seismic & Reservoir Characterization - Performed seismic attribute analysis, geo-hazard evaluation, and reservoir modeling across Gulf of Mexico and Azerbaijan deepwater assets. Supported well placement and subsalt drilling risk mitigation using No Drilling Surprises (NDS).

• Advanced Drilling Support & Team Leadership - Monitored real-time drilling data including mud loss/gain, fracture zones, and early kick detection. Provided technical mentoring, MPD-certified guidance, and presented geoscience workflows to cross-functional teams.

• Data Analytics & Workflow Automation: Engineered statistical and Machine Learning workflows to detect drilling patterns and automate offset well analysis. Streamlined data extraction from Well Vantage and automated uploads to Drillworks using web scraping techniques.
• Real-Time Pore Pressure Modeling & Wells Monitoring: Delivered pre-drill PPFG models and real-time subsurface hazard assessments for GOM and Suriname deepwater wells. Monitored casing tests, trip plots, FIT, LOT and DFIT to create daily operations reports and post-well lookbacks.
• Drilling Risk Mitigation & Prospect Evaluation - Developed WBS models and proposed risk mitigation strategies for optimized well trajectories. Collaborated with geoscience teams to assess well placement and conducted 3D mapping and seismic interpretation for Cuitlacoche, Abeline (GOM), and Zandrij-1 South (Suriname).
• Cross-Functional Communication & Knowledge Transfer - Provided technical insights for RTOC reports and rig decision-making. Participated in rig and subsurface meetings, trained junior staff, and collaborated with PE, RE, and DE teams for drilling performance optimization.

Project - Automation of Industrial Process
• Clustering & Industrial Analytics - Applied KMeans and GMM clustering for alarm categorization in oil refineries, customer segmentation, and production trend analysis for (GOM). Delivered actionable insights to enhance operational efficiency and inform marketing strategies.

• Time Series Forecasting & Predictive Modeling - Conducted time series analysis for seasonality/ Trend detection in BASF and oil production data for GOM. Applied supervised ML (logistic regression, SVM, decision trees, gradient boosting) for log facies classification, and developed ANN/CNN models using TensorFlow/Keras for image-based applications.

• Statistical Analysis & Experimental Design - Performed hypothesis testing, t-tests, and confidence interval analysis on cardiovascular datasets to detect anomalies and support predictive healthcare modeling for early-stage heart failure detection.

• Real-Time Data Analytics & Visualization: Supported real-time operations by mining, cleaning and visualizing high-volume drilling datasets using exploratory data analysis (EDA), SQL queries, Excel Pivot Tables, and Python-based analytics to improve operational decision making.
• Feature Engineering & Machine Learning: Engineered features, and applied dimensionality reduction, on offset well data to develop facies classification models. Translated insights into dashboards for predictive drilling and planning optimization.
• AI Modeling & Emerging Technologies: Built AI models to compare best well performance KPI. Gained exposure to Agentic AI development for SaaS-based real-time monitoring platforms tailored to client-specific operational queries.

• PPFG & Wellbore Stability Modeling - Monitored real-time drilling operations and performed PPFG and WBS modeling for Chevron (GOM), ExxonMobil (Guyana), and Repsol (Colombia) offshore projects. Delivered tensile failure and collapse curves to support wellbore stability assessments and safe drilling execution.

• Seismic Interpretation & Subsurface Risk Analysis - Conducted seismic interpretation and hazard evaluation for unconventional Budha Limestone and Austin Chalk wells in Southeast Texas. Generated subsurface maps and applied severity matrix modeling to optimize well trajectories and reduce operational risk.

• AI-Powered Predictive Alerts & Cloud Integration: Configured Petro Vault HD SaaS system for predictive alerts and event monitoring, enabling preventive actions to mitigate drilling risks.

• Well Planning & Risk Management - Led Single Well Development & Execution (IFO compliance), defined value-based well objectives, and conducted uncertainty analysis and subsurface hazard assessments for multi-trajectory wells in GOM (Sicily, Jack/St. Malo, Anchor, Sweetwater, Stampede).

• Seismic Interpretation & Subsurface Modeling - Performed seismic, structural, and stratigraphic interpretation; conducted AVO analysis, seismic inversion, and VSP planning. Applied exploratory data analysis (EDA) techniques on seismic and log data to identify structural patterns and reservoir heterogeneity.

• Geomechanics, Formation Evaluation & EDA - Delivered pre-drill PPFG and 1D geomechanical models; performed tensile/shear failure analysis, wellbore stability simulations, and interpreted LOT/FIT/DFIT data. Used EDA methods to assess rock properties and evaluate formation behavior in subsalt environments.

• Operational Oversight & Regulatory Reporting - Supervised wellsite geologists, compiled daily G&G reports, and submitted exploration plans to BSEE. Led rig-based communication and presented end-of-well lookbacks and risk summaries to Chevron stakeholders.

• Innovation, Training & Strategy Alignment - Piloted geoscience software evaluations and collaborated on implementation strategies. Conducted seismic-to-well calibration workshops and presented business cases for technology integration and data-driven decision frameworks.

• Seismic Inversion & Reservoir Characterization - Performed log data QC, editing, and conditioning; generated synthetic seismograms, conducted fluid substitution, and applied AVO inversion to characterize target sands and reservoir properties.

• Geophysical Modeling & 3D Subsurface Visualization - Developed velocity models and applied seismic inversion for lithology and fluid distribution. Created 3D geobodies for reservoir interpretation using integrated seismic and well data.

• Fracturing Analysis & Structural Interpretation - Assessed brittleness for sweet spot identification in West Texas unconventional plays. Conducted salt body mapping, dip/amplitude analysis, and delivered seismic interpretation for the Avalon Project. Served as SME for seismic-to-well calibration workflows.

• Data-Driven Geophysical Interpretation - Applied exploratory data analysis (EDA) on log and seismic attributes to identify lithological variations and fluid signatures, improving inversion model accuracy and well placement strategies.

• Seismic Inversion & Reservoir Characterization - Led AVO, LMR inversion, and fluid substitution modeling for Eagle Ford, West Texas, and Gulf of Mexico plays (conventional and unconventional). Delivered Lambda-Rho/Mu-Rho analysis for lithology and fluid discrimination.

• Velocity Modeling & Pressure Prediction - Applied 2nd and 4th order RMO corrections, seismic-to-well calibration, and VTI velocity modeling to support AVO inversion, pore pressure estimation, and reservoir risk assessment.

• Seismic Conditioning & Inversion Workflows - Executed pre- and post-stack seismic inversion, amplitude balancing, and geomechanically property extraction to refine subsurface models and improve reservoir quality prediction.

• Acquisition Design & Field Processing Oversight - Managed 2D/3D seismic acquisition in land, marine, and transition zones across North America and the Middle East. Supervised data QC, parametrization, deconvolution, noise attenuation, and PSTM workflows.