Course Introduction
The oil and gas industry generates large volumes of geological, drilling, completion, production, reservoir, equipment, maintenance, commercial, and operational data that must be converted into reliable intelligence for better technical and business decisions. This Oil and Gas Data Analytics and Production Intelligence Training Course provides a structured, practical approach to analyzing upstream oil and gas information, with particular emphasis on production performance, well behavior, field trends, operational efficiency, forecasting, decline analysis, and production optimization. Modern public energy datasets demonstrate the breadth of available information, including production, reserves, drilling activity, producing-well counts, well production rates, and market-related measures.
The course begins by establishing an integrated oil and gas data analytics framework covering exploration, drilling, completion, production, processing interfaces, asset management, and field operations. Participants examine how information from production accounting systems, SCADA, historians, well tests, flow meters, laboratory systems, drilling databases, maintenance systems, reservoir models, and external energy datasets can be combined for analysis. BOEM, for example, provides production information at lease, well, and operator levels, including oil, condensate, gas, water production, producing completions, and related production records, illustrating the multidimensional nature of oil and gas production analytics.
Production intelligence is a central theme throughout the program. Participants learn to analyze oil, gas, water, and condensate production; production rates; well uptime; operating conditions; production allocation; decline behavior; artificial-lift indicators; and field-level performance. EIA's current oil and natural gas datasets include monthly production information, drilling activity, production by well-rate categories, producing-well information, and other upstream indicators. These data structures provide useful examples for understanding how production trends can be evaluated across wells, fields, regions, technologies, and time periods.
The program also develops analytical techniques for identifying production losses and understanding changes in well and field performance. Participants explore decline-curve concepts, production forecasting, anomaly detection, well ranking, production benchmarking, downtime analysis, water-cut and gas-oil-ratio trends, operating-condition analysis, and root-cause investigation. The training emphasizes distinguishing geological or reservoir-driven changes from operational issues, equipment failures, measurement problems, maintenance events, and other factors that influence observed production. DOE research explicitly identifies data analytics as an area supporting improved ultimate recovery and operational efficiency in oil and gas resources.
Beyond individual wells, the course develops field and portfolio-level production intelligence. Participants learn how to compare assets, identify high- and low-performing wells, evaluate drilling and completion outcomes, monitor production against expectations, analyze operational trends, and connect production performance with capital and operating decisions. Drilling data can include rig activity, footage drilled, well counts, well depth, and drilling costs, while production datasets can provide oil, gas, condensate, and water measures. This creates opportunities to analyze the relationship between development activity, well characteristics, production rates, and overall field performance.
The final component is an applied oil and gas production intelligence project in which participants integrate well, production, operational, drilling, maintenance, and contextual datasets into an end-to-end analytical solution. The project can include production trend analysis, well segmentation, decline forecasting, anomaly identification, production-loss investigation, performance benchmarking, and management dashboards. Participants finish with a practical framework for turning complex upstream datasets into actionable intelligence that supports production optimization, asset management, operational planning, forecasting, and evidence-based decision-making.
Duration
5 days
Who Should Attend
-
Oil and gas production managers responsible for production performance, operational reporting, field optimization, and production targets.
-
Petroleum engineers seeking stronger capabilities in production analytics, well performance analysis, forecasting, and data-driven optimization.
-
Reservoir engineers working with production history, decline behavior, reservoir performance, field trends, and production forecasting.
-
Drilling and completion professionals interested in evaluating well delivery, production outcomes, drilling performance, and development trends.
-
Production engineers and operations engineers responsible for well surveillance, production optimization, artificial lift, and field performance.
-
Oil and gas data analysts, BI professionals, and data scientists working with production, operational, equipment, and asset datasets.
-
Asset managers and field managers requiring analytical tools for well ranking, production benchmarking, performance monitoring, and investment decisions.
-
Operations and maintenance professionals analyzing equipment reliability, downtime, failures, work orders, and production-impacting events.
-
Energy economists, commercial analysts, and planning professionals connecting production intelligence with operational and business performance.
-
Oil and gas regulators, government energy professionals, and public-sector analysts working with production, reserves, drilling, and industry-performance information.
-
Digital transformation, automation, SCADA, and industrial analytics professionals supporting data-driven oil and gas operations.
-
Consultants, researchers, technology professionals, and technical advisors involved in upstream analytics, production optimization, and energy-sector intelligence.
Course Objectives
-
Develop a comprehensive oil and gas data analytics framework covering wells, reservoirs, drilling, completions, production, operations, equipment, maintenance, and field-level performance.
-
Integrate production, well, drilling, completion, reservoir, equipment, maintenance, operational, and contextual datasets into consistent analytical structures for reliable decision-making.
-
Analyze oil, natural gas, condensate, and water production trends at well, field, asset, regional, and portfolio levels using appropriate production and performance indicators.
-
Apply production analytics methods to identify declining wells, abnormal production behavior, downtime, operational losses, changing water production, and other performance issues.
-
Develop well and field production forecasts using historical production, decline behavior, operational conditions, development activity, and relevant explanatory variables.
-
Evaluate drilling and completion performance by linking well characteristics, development activity, production outcomes, costs, timing, and post-completion performance indicators.
-
Apply segmentation and benchmarking techniques to compare wells, fields, assets, production categories, operating conditions, and performance groups for targeted optimization.
-
Investigate production losses and anomalies using operational events, equipment conditions, maintenance history, measurement information, and production trends to support root-cause analysis.
-
Build oil and gas production dashboards that communicate production volumes, rates, well performance, decline trends, downtime, forecasts, exceptions, and operational KPIs.
-
Complete an integrated production intelligence project that transforms multi-source upstream data into actionable insights for production optimization, asset management, forecasting, and strategic decisions.
Comprehensive Course Outline
Module 1: Oil and Gas Data Analytics and Production Intelligence Foundations
-
Examine the upstream oil and gas value chain and the role of analytics across exploration, drilling, completions, production, operations, maintenance, processing interfaces, and asset management.
-
Explore major oil and gas data domains including well information, production volumes, pressure, temperature, fluid properties, drilling activity, equipment status, maintenance events, and operational records.
-
Define core production intelligence KPIs covering production rate, cumulative production, uptime, decline, water cut, gas-oil ratio, well utilization, downtime, and production variance.
-
Establish an analytical framework connecting well-level information with field, asset, portfolio, operational, financial, and strategic performance decisions.
Module 2: Oil and Gas Data Integration, Preparation and Quality Management
-
Integrate production accounting, SCADA, historians, well databases, drilling systems, maintenance platforms, laboratory records, reservoir information, and external energy datasets.
-
Apply data-quality controls for missing production records, duplicate measurements, inconsistent units, timestamp issues, abnormal readings, meter discrepancies, and incomplete well histories.
-
Develop consistent well, completion, facility, field, operator, production-period, and asset identifiers to support reliable cross-system analytics and performance comparisons.
-
Build repeatable data preparation workflows that improve traceability, validation, documentation, analytical reproducibility, and confidence in production intelligence.
Module 3: Well Production Analytics and Performance Monitoring
-
Analyze oil, gas, condensate, and water production at daily, weekly, monthly, and annual levels to identify trends, variability, production cycles, and changes in well behavior.
-
Evaluate well production rates, cumulative output, operating time, downtime, water production, gas-oil ratio, and other indicators relevant to production surveillance.
-
Segment wells by production performance, maturity, operating characteristics, decline behavior, fluid characteristics, and other analytical dimensions for targeted investigation.
-
Develop well-performance scorecards and monitoring frameworks that identify high-value assets, underperforming wells, production exceptions, and emerging performance risks.
Module 4: Production Decline, Reservoir Performance and Forecasting Analytics
-
Apply decline-analysis concepts to historical well-production data and investigate production trajectories, decline rates, inflection points, and changing well performance.
-
Develop production forecasts using historical trends, decline behavior, operating conditions, development assumptions, and appropriate analytical or statistical approaches.
-
Compare forecast and actual production to identify deviations, forecast bias, unexpected decline, operational disruptions, and changes in production behavior.
-
Construct field-level production outlooks by aggregating well forecasts and incorporating new wells, workovers, interventions, downtime, and development schedules.
Module 5: Drilling, Completion and Development Performance Analytics
-
Analyze drilling activity, well delivery, development timing, well depth, drilling performance, and completion information to understand development efficiency and production outcomes.
-
Connect drilling and completion characteristics with subsequent production performance to evaluate well productivity, development effectiveness, and performance variation.
-
Compare wells and development campaigns using production rates, time to first production, production ramp-up, downtime, costs, and other relevant performance measures.
-
Develop analytical frameworks for evaluating development scenarios, well prioritization, drilling schedules, production expectations, and post-completion performance.
Module 6: Production Optimization, Artificial Lift and Operational Intelligence
-
Analyze operating conditions and production trends to identify opportunities for well optimization, artificial-lift adjustments, operating changes, workovers, and other interventions.
-
Investigate relationships among pressure, flow, temperature, lift performance, equipment conditions, fluid properties, and production behavior using structured analytical methods.
-
Identify recurring production constraints, operating bottlenecks, unstable wells, equipment-related losses, and abnormal production patterns through time-series and event analysis.
-
Prioritize production-improvement opportunities using quantified production impact, well potential, intervention history, operational constraints, asset criticality, and expected recovery.
Module 7: Production Loss, Downtime and Maintenance Analytics
-
Analyze downtime records, maintenance events, equipment status, work orders, production interruptions, and operational events to quantify their impact on oil and gas production.
-
Develop production-loss classifications that distinguish equipment failures, planned maintenance, process constraints, operational events, reservoir conditions, measurement issues, and other causes.
-
Apply anomaly detection and root-cause analysis to identify recurring production interruptions, abnormal equipment behavior, and emerging operational risks.
-
Connect maintenance and reliability analytics with production performance to support intervention prioritization, maintenance planning, equipment strategies, and production recovery.
Module 8: Field, Asset and Portfolio Production Intelligence
-
Compare production performance across wells, fields, facilities, assets, operators, regions, development campaigns, and other organizational or technical groupings.
-
Analyze production concentration, well contribution, asset maturity, decline exposure, production variability, and performance distribution to understand portfolio characteristics.
-
Develop scenario analyses for new wells, workovers, production interventions, facility constraints, decline assumptions, development schedules, and changing operating conditions.
-
Translate field and portfolio analytics into actionable intelligence supporting production planning, capital allocation, asset management, operational strategy, and performance improvement.
Module 9: Oil and Gas Production Dashboards, KPIs and Executive Intelligence
-
Design production dashboards covering oil and gas volumes, production rates, cumulative output, well performance, decline, downtime, losses, forecasts, and operational exceptions.
-
Create visualizations for well ranking, field trends, production distributions, decline curves, forecast-versus-actual performance, and production-loss analysis.
-
Develop role-specific reporting for production engineers, field managers, asset managers, executives, planners, maintenance teams, and commercial stakeholders.
-
Establish performance-monitoring workflows using thresholds, alerts, exception reporting, trend analysis, automated KPI refreshes, and recurring production intelligence reviews.
Module 10: Capstone Oil and Gas Data Analytics and Production Intelligence Project
-
Integrate well, production, drilling, completion, maintenance, operational, and contextual datasets into a structured end-to-end production intelligence solution.
-
Diagnose well and field performance using production trends, decline analysis, anomaly detection, downtime analysis, benchmarking, and production-loss investigation.
-
Develop a production intelligence dashboard presenting well performance, field production, forecasts, production losses, exceptions, performance rankings, and management KPIs.
-
Present an integrated production optimization strategy that converts analytical findings into practical actions for wells, operations, maintenance, field planning, asset management, and production performance improvement.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
