Reservoir and production engineers
Sample topic from the class:
“Gain Insights Into Long-Term Performance Using Various DCA Tools”
This two-and-half-day workshop entails a fundamental understanding of well performance with the use of several tools, such as RTA and DCA. Application of DCA emphasizes matching the cumulative- production curve for retaining solution consistency and objectivity. Overall, suitability of these tools for reserves forecasting will be the cornerstone of this workshop. We will also introduce a promising semi-analytical DCA tool, the Series model. Although deterministic reserves estimation will be emphasized, probabilistic approaches will be outlined.
Obtaining some of the basic reservoir parameters with DFIT entails stress and reservoir properties, such as initial pressure and permeability. However, factors influencing the non-ideal DFIT behavior often present interpretation challenges. We will explore some of these issues while tackling some of the field responses. Finally, beyond the early production period, production of water can complicate the lift issue. We will discuss a simplified plunger-lift model to tackle this flow problem at hand. Tools involved include Kappa (RTA and PTA modules), and simple analytical diagnostic and analysis methods.
- Explore diagnostic fracture injection testing (DFIT) and well management before production initiation
- Forecast performance with decline-curve analysis (DCA) tools and understand their relative strengths
- Use rate-transient analysis (RTA), when possible, to gain insights into long-term performance
- Consider merits of reservoir simulation approach
- Estimate reserves with a few tools in both deterministic and probabilistic frames
- Understand the wellbore lift issue with a plunger-lift
- Solution workflows for participants’ specific problems
- Participants discuss operational problems on pertinent topics within the workshop’s scope
- Background review of each topic
- Hands-on problem-solving sessions using field data – preference: client’s own data