The economics of well testing have changed. A conventional interpretation takes an experienced engineer hours to days per test, which is affordable when a field produces a handful of tests a year. It is not affordable when permanent gauges generate a continuous record from every well and the asset holds fifty producers. The result in most organisations is that the data is stored and never examined, or examined only when a well has already failed and someone goes looking for a cause after the fact.

The practical answer is to separate screening from interpretation. Screening processes every well the same way: clean the data, reconstruct the rate history, find the shut-ins, compute the derivative, extract a permeability and skin estimate, and record the result. It does not need to produce a definitive interpretation. It needs to be consistent, repeatable and applied to everything, so that the values it produces can be compared between wells and tracked over time. A skin that has doubled over eighteen months is a finding regardless of whether the absolute value is exactly right.

This work is dominated by data handling rather than by reservoir physics. Gauges drift, fail and record through periods when the well was not doing what the production database says it was. Rate allocation is imperfect, and a pressure response cannot be interpreted against a rate history that is wrong. Filtering that reduces a year of one-second data to a manageable size can remove exactly the early-time behaviour the interpretation depends on. Getting these steps right is the difference between a screening workflow that surfaces real problems and one that generates noise. This course is built around that reality.

By the end of this training, participants will be able to:

• Assess permanent gauge and well test datasets for quality, drift, gaps and sensor failure
• Apply filtering and data reduction methods that preserve transient behaviour while making datasets manageable
• Reconstruct rate histories from production and allocation data and reconcile them with the pressure record
• Detect shut-in periods and valid build-ups automatically within a long pressure record
• Compute superposition time functions correctly for variable rate histories
• Calculate pressure derivatives consistently across many wells with controlled smoothing
• Generate diagnostic plots and extract screening estimates of permeability, skin and drainage volume
• Apply rate transient analysis methods to long-term production data across a well population
• Track changes in derived parameters over time and identify wells requiring detailed investigation
• Build repeatable surveillance workbooks that process new data as it arrives

The course is delivered as an applied data programme built around processing real gauge and production datasets. Each stage of the workflow is developed as a spreadsheet build, applied first to a single well and then extended across a population, so that participants see where a method that works on one dataset fails on fifty. Poor quality data is used deliberately, including records with gauge drift, missing rate history and undocumented well events, so that the handling of imperfect data is learned rather than assumed away. The relationship between screening output and full interpretation is addressed throughout.

• Organisations sending participants to this training will:
• Extract value from gauge and test data that is currently stored and never analysed
• Detect skin growth, productivity decline and connectivity changes before they become production losses
• Screen an entire well population consistently instead of interpreting a few wells thoroughly
• Prioritise intervention and detailed study effort on the wells that justify it
• Improve the quality and consistency of surveillance reporting
• Build repeatable workflows that survive staff turnover

Participants will:

• Handle large pressure and rate datasets confidently without corrupting them
• Build automated diagnostic and screening workflows rather than repeating manual analysis
• Recognise data quality problems that would invalidate an interpretation
• Track well performance parameters over time and spot meaningful change
• Produce surveillance output that engineers and managers act on
• Free time for the interpretation work that genuinely requires judgement

• Reservoir and production engineers responsible for well surveillance
• Well test engineers handling large volumes of transient data
• Production surveillance and data analysts in subsurface teams
• Petroleum engineers working with permanent downhole gauge installations
• Field development and asset engineers monitoring well performance
• Engineers inheriting large historical datasets that have never been processed
• Technical supervisors building surveillance workflows for an asset

Upon successful completion of this training course, delegates will be awarded an official Certificate of Completion issued by the Petroleum Engineers Association (PEA), an ISO 9001:2015 certified training organization. The certificate carries 10 Credits and formally records the total learning hours completed.

Each certificate is signed by the Course Facilitator and the CEO of the Petroleum Engineers Association, and serves as verifiable proof of professional training that delegates can present to employers and professional bodies worldwide.