Soultz-sous-Forêts Geothermal Reservoir: Structural Model Update and Thermo-Hydraulic Numerical Simulations Based on Three Years of Operation Data

The geothermal powerplant of Soultz-sous-Forêts (France) is investigating the possibility of producing more energy with the same infrastructure by reinjecting the geothermal fluid at lower temperatures. Indeed, during the operation of the powerplant, the geothermal fluid is currently reinjected at 60–70 °C in a deep fractured granite reservoir, and the MEET project aims to test its reinjection at 40 °C. A 3D hydrothermal study was performed in order to evaluate the spreading of the thermal front during colder reinjection and its impact on the production temperature. In the first step, a 3D structural model at fault scale was created, integrating pre-existing models from 2D vintage seismic profiles, vertical seismic profiles, seismic cloud structure and borehole image logs calibrated with well data. This geometrical model was then adapted to be able to run hydrothermal simulation. In the third step, a 3D hydrothermal model was built based on the structural model. After calibration, the effect of colder reinjection on the production temperature was calculated. The results show that a decrease of 10 °C in the injection temperature leads to a drop in the production temperature of 2 °C after 2 years, reaching 3 °C after 25 years of operation. Lastly, the accuracy of the structural model on which the simulations are based is discussed and an update of the structural model is proposed in order to better reproduce the observations.

Taming the Thunder Horse With Axes and Vectors

The Thunder Horse Field targets Middle Miocene deepwater turbiditic reservoirs. Despite being prolific, the mapping of the ~180 m thick, partly amalgamated reservoir sandstones is challenging. Seismic quality is reduced by the presence of salt structures. The salt overburden and high formation pressure require the use of heavy mud weights and oil-based drilling fluids, which limit the resolution and interpretation potential of borehole image logs (BHI). Halokinetic movements caused significant post-depositional deformation of the already complex gravity-driven sediment stack, and the reservoir beds drape against an E-W oriented salt wall. Consequently, the assessment and removal of the structural dip component are not trivial, and the evaluation of paleo-transport directions is considerably more complicated compared to undisturbed deepwater reservoirs. This paper illustrates the potential of eigenvector methods to BHI from Ruehlicke et al. (2019) for reconstructing the depositional slope and the architecture of mass transport complexes in the case of chaotic depositional settings and uncertain structural dip. Figures from Henry et al. (2018) are used wherein part axial analysis was performed on data from a group of Thunder Horse wells and presented in more detail.

Automated Verification of Sidewall Core Recovery Depth using Borehole Image Logs

Sidewall coring is a cost-effective process to complement conventional fullbore coring. Because sidewall cores target exact depth points, verification of the sidewall core recovery depth is required. We present an automated, fast workflow to perform the depth verification using borehole images, thereby providing consistent results. An application example using a typical dataset is used to showcase the workflow. A novel automated approach based on image analysis techniques and Bayesian statistical analysis is developed to verify sidewall core recovery depth using borehole image logs. A complete workflow is presented covering: 1) utilization of reference logs, e.g., gamma ray, to correct image log depth using cross correlation and/or dynamic time warping, 2) automated identification of sidewall core cavity in borehole image log using the circle Hough transform, and 3) estimation of confidence in the identification using Bayesian statistics and specialized metrics. The workflow is applied on a typical dataset containing tens of sidewall core cavities with varying quality. Results are comparable to the manual interpretation from an experienced engineer. A number of observations are made. First, the use of reference logs to correct the image log allows for determining the exact well logs values where the sidewall core was sampled, which is then compared to the initial target well logs values. This increases the confidence that the target lithofacies was sampled as planned. Second, the circle Hough Transform is suitable for this problem because it provides stable solutions for partially imaged sidewall core cavities typical in pad-based borehole images. Third, the use of Bayesian statistics and specialized metrics for the problem, such as average and standard deviation borehole image intensity in the cavity, provides customizability to work with multiple types of borehole images and with varying initial depth guess uncertainties. Overall, the use of fast and automated methodology for depth verification opens up avenues for near real-time combined sidewall coring, imaging, and verification workflows. The novelty in this study lies in using a combination of image processing techniques and statistical analysis to automate an established manual workflow. The automated workflow provides consistent results in minutes rather than hours. Results also incorporate a confidence index estimation.

An Integrated Approach for Formation Micro-Image Rock Typing Based on Petrography Data: A Case Study in Shallow Marine Carbonates

Core rock-typing (RT) is commonly used for creating geologically reliable models of porous media in carbonate reservoirs. This approach is more advanced than the traditional porosity–permeability relationship and is based on the division of carbonate rocks into groups, using common classifications (lithofacies, FZI, Winland–Pittman, etc.). These clustering methods can provide either geological or petrophysical descriptions of the identified rock types. Besides, the connection of identified core rock types with standard logs could be challenging due to the different scales of measurement. This paper considers the creation of a new approach, named “integrated rock-typing,” which connects geologically and petrophysically driven rock types using borehole image logs. The methodology was applied to an Upper Devonian–Lower Carboniferous carbonate field. The workflow comprises borehole image structural/textural analysis with vug fraction identification, quantitative geological descriptions from thin sections, and petrophysical measurements. The geological section is divided into six rock types, which were controlled by sedimentary and diagenetic processes. The created Rock Type Catalogue provides clear links between rock types and log data, including wells with standard suites of logs. The results will be useful for geological modelling and validation of the future drilling strategy for the studied field.

TAMING THE THUNDER HORSE WITH AXES AND VECTORS

The Thunder Horse Field targets Middle Miocene deepwater turbiditic reservoirs. Despite of being prolific, the mapping of the ~180 m thick, partly amalgamated reservoir sandstones is challenging. Seismic quality is reduced by the presence of salt structures. The salt overburden and high formation pressure requires the use of heavy mud weights and oil-based drilling fluids, which limit the resolution and interpretation potential of borehole image logs (BHI). Halokinetic movements caused significant post-depositional deformation of the already complex gravity- driven sediment stack and the reservoir beds drape against an E–W oriented salt wall. Consequently, the assessment and removal of the structural dip component is not trivial and the evaluation of paleo-transport directions is considerably more complicated compared to undisturbed deepwater reservoirs. The intention of this paper is to bring the main results from Henry et al. (2018) into context with the eigenvector methodology from Ruehlicke et al. (2019) and to emphasize its value for reservoir characterization.

An Operators Investigation of Performance Drivers Using Diagnostics and Data Analytics

In multi-stage plug-and-perf horizontal well completions, there are a multitude of moving parts and variables to consider when evaluating performance drivers. Properly identifying performance drivers allows an operator to focus their efforts to maximize the rate of return of resource development. Typically, well-to-well comparisons are made to help identify performance drivers, but in many cases the differences are not clear. Identifying these drivers may require a better understanding of performance variability along a single lateral. Data analytics can help to identify performance drivers using existing data from development activities. In the case study below, multiple diagnostics are utilized to identify performance drivers. A combination of completion diagnostics including oil and water tracers, stimulation data, reservoir data, 3D seismic, and borehole image logs were collected on a set of wells in the early appraisal phase of a field. Using oil tracers as the best indication of stage level performance along the laterals, data analytics is applied to uncover the relationships between the tracers and the numerous diagnostics. After smoothing was applied to the dataset, trends between oil tracer recovery, several independent variables and features seen in image logs and 3D seismic were identified. All the analyses pointed to decreasing tracer recovery, and likely decreased oil production, near faulted areas along each lateral. A random forest model showed a moderate prediction power, where the model's predicted tracer recovery on blind stages was able to explain 54% of the variance seen in the tracer response (r2=0.54). This analysis suggests the identification of certain faulted areas along the wellbore could lead to ways of improving individual well economics by adjusting completion design in these areas.

Open fractures in pre-salt silicified carbonate reservoirs in block BM-C-33, the Outer Campos Basin, offshore Brazil

Natural open fractures are present in sidewall cores and in whole core samples from pre-salt reservoirs in the license BM-C-33 in the Campos Basin, Brazil. Open fractures are also observed in borehole image logs, and fracture densities are in general high. The highest density of open fractures is seen in the damage zones above and below larger cavities (Amalgamated Cavern Damage Zones - ACDZs). Outside the ACDZs the fracture density is high in silicified carbonates, where it tends to increase with decreasing porosity. Clean dolomites are less fractured than the silicified interval while the less brittle argillaceous dolomites have the lowest fracture density. Some fractures appear vuggy on borehole image logs and fracture densities are high close to vugs and larger cavities. The positive correlation between fractures and vugs is caused by flow of dissolving fluids through open fractures, and fracturing at stress concentrations around vugs, Two major fault zones have been interpreted from borehole image logs which have damage zones with very high fracture density. The well test permeability is much greater than the matrix permeability estimated from sidewall core and log measurements. This excess permeability is attributed to fractures, in combination with caverns and intervals with frequent vugs.