Session 3C: Reservoir/Production

A geothermal conceptual model reflects our understanding of reservoir processes and is continuously refined and updated as the reservoir evolves over time. Since the commencement of its commercial production in 1982, Kamojang geothermal field has been gathering numerous static and dynamic data from new well drilling and continuous monitoring of the reservoir's responses to various development scenarios. Changes to the interpreted reservoir boundaries, structures, and reservoir interconnectivity are examples of what have been made to Kamojang conceptual model over the course of its exploration and development phases. Reservoir pressure is one of the most important dynamic data to have to interpret the fluid flows and permeability in a geothermal reservoir. Furthermore, in dry steam reservoirs such as Kamojang with currectly low observable superheat, reservoir pressure is directly related to enthalpy and potential for steam production. This paper presents the effort of data processing and analysis of Kamojang reservoir pressure distribution that was mapped from 66 wells distributed throughout Kamojang geothermal field over the time span of about 42 years. The observed reservoir pressure behavior shows multiple pressure regions exists in Kamojang and each differs in pressure magnitude that is increasing from the West to the East part of Kamojang with all the regions sharing similar reservoir pressure decline. This pressure behavior implies effective lateral permeability between each pressure region and fluid flows from the East toward the West of the reservoir. As the East side of Kamojang is characterized with high reservoir and shut in pressure suggesting that the area is connected to the upflow, interpreting the location of the upflow in a dry steam reservoir requires multidisciplinary analysis. Therefore this analysis is still needed to be integrated with other disciplines to validate this finding and further refine the Kamojang conceptual model.

Harnessing geothermal energy for power generation in sedimentary basins has traditionally faced significant challenges, primarily due to the low permeability of formations and the narrow margin of thermodynamically favorable conditions. However, recent technological advancements, particularly those adapted from the oil and gas industry, have made it possible to extract heat from deep sedimentary formations at lower temperatures than previously considered feasible. The Deep Earth Energy Production Corp. (DEEP) geothermal project, located in the Williston Basin of southeastern Saskatchewan, Canada, exemplifies these advancements. To support the development of a 5-MW-gross pilot geothermal project, DEEP has conducted surface exploration and subsurface interrogation activities to characterize the geothermal resource and its ability to support the development of geothermal power. This paper presents an integrated multi-segment wellbore model coupled with a thermal simulation framework in INTERSECT* to assess the geothermal resource performance for the DEEP project.

This approach offers several improvements, including more accurate calculations of wellbore pressure gradients, enhanced crossflow modeling, and improved wellbore storage representation. Importantly, it allows for a precise depiction of heat transfer with surrounding formations and thermal interference between the cased sections of horizontal production and injection doublets. These advancements are critical for validating the feasibility of low-temperature geothermal resources, as even small variations in the pressure and temperature of geothermal brine can significantly impact the long-term viability of the project. The model accurately captures the thermal effects of cold water reinjection and wellbore heat loss on production fluid temperature, enabling the exploration of various production rates, injection temperatures, reservoir permeabilities, wellbore trajectories, and conductive heat transfer rates within the cased sections of the wells. This allows for a detailed quantification of their respective impacts on the thermodynamics of the production fluid.

The PGV power plant was restarted in 2020 following the 2018 Kilauea eruption, providing a unique opportunity to quantify the impacts of this eruption on permeability, temperature, and pressure in the geothermal reservoir.

Permeability was quantified using multiple datasets which shows reduced permeability in some production fractures but overall good permeability remaining in others which has led to a very successful recovery drilling campaign and plant restart.

A numerical model was developed which simulates the pre-eruption and post-eruption reservoir behavior. The numerical model was calibrated to the historical reservoir performance and the unique effects of the eruption, including temperature recovery and changes to the permeability distribution. The resulting model accurately matches the post-eruption temperature recovery and the reservoir pressure response to the plant restart under the modified permeability regime.

The Sorik Marapi Geothermal Field is a volcano-hosted geothermal system, located in northwestern Sumatra, Indonesia. As the field development and operations have expanded over the past several years, the conceptual model has been continuously updated to represent the geologic data from new drilling and well testing results. The numerical reservoir model has also been updated to incorporate the geoscientific understanding from the conceptual modeling work, drilling and well testing results, and field operations. The numerical model was developed within the iTOUGH2 framework for automatic calibration, and a joint inversion of steady-state data (i.e., natural state) and transient production data was performed to adjust model input parameters. The calibrated numerical model demonstrates reasonable matches against the natural state pressures and temperatures and the available monitoring data during wellfield operations. The current numerical model provides a suitable basis for assessing the production capacity of the resource area and will be used to forecast the reservoir response to various development scenarios.

The study begins with an overview of geothermal wells and the common challenges faced in geothermal operations due to pressure drawdown. A critical operational question is whether the drawdown is due to scaling or bottom hole pressure decrease, which determines whether the well should be cleaned or if a new well needs to be drilled. The paper introduces the Monte Carlo Particle Filter and the wellbore model, detailing their theoretical foundations and computational methodology. The wellbore model simulates the complex interactions between geothermal fluid and the wellbore environment under varying operational conditions, identifying critical factors influencing scaling.
By analyzing data from existing geothermal wells alongside simulations conducted through the model, the research validates its effectiveness in predicting scaling occurrence and bottom hole pressure drawdown. Furthermore, the model offers insights into other well parameters, such as enthalpy, pressure, and flow rate adjustments.

In the Lumut Balai geothermal field, daily well production flowrates and enthalpy measurement data are not available due to the absence of two-phase flowmeters. This condition complicates quantitative estimations regarding steam availability, steam production decline rates, and subsequently steam supply forecast. Meanwhile, a quarterly Tracer Flow Testing (TFT) has been performed to monitor individual well production flowrates and enthalpy which allows merely a qualitative evaluation of production performance. These uncertainties significantly impact reservoir management strategies.

The Steam Allocation Lumut Balai (SALB) application has been developed to estimate daily individual well production by solving mass and energy balance equations throughout the field process flow diagram and integrating operational data such as wellhead pressure, separator pressure, brine mass flow rate, steam mass flow rate, re-injected mass flow rate, and TFT. This daily monitoring facilitates a nuanced understanding of the wells and the reservoir behavior, expediting the troubleshooting and the resolution of the issues. This paper outlines the methodology employed in the SALB application and details its implementation.