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.

Integration Applications of Image and Sonic Data in the Fault-Dominated Carbonate Reservoir in Tarim Basin

Carbonate reservoir is one of the most complex and important reservoirs in the world. It was confirmed that the slip-strike fault played a crucial role in the fault-dominated carbonate reservoir in Tarim basin. It is challenging to evaluate this kind of reservoir using the open-hole log or seismic data. Identifying and characterizing the fault-dominated carbonate reservoir were the objectives of this case study. High-definition borehole resistivity image and dipole sonic logs were run in several wells in the research area. It was revealed the detail features of the fault-dominated carbonate reservoir, such as natural fractures, faults or breccias. Compared with the typical geological model of strike-slip faults and outcrop features, the characteristics of the breccia zone and the fracture zone in the strike-slip fault system were summarized from the borehole image interpretation. A unique workflow was innovated with the integration of image and sonic data. Breccias and fractures were observed in the borehole image; and reflections or attenuations in Stoneley waveforms can provide indicating flag for permeable zones. Integrated with the other related geological data like mud logging or cores, the best pay zones in the fault-dominated carbonate reservoir were located. The characteristics of the strike-slip fault was revealed with the integration of the full-bore formation microimager and dipole shear sonic imager data. The fault core was a typical breccia zone with strong dissolution, which showed good potential in permeability, but it was found that some fault cores were filled with siliceous rock or intrusive rock. The features of the fillings in the fault zone were described based on the image and sonic data. The side cores or geochemical spectroscopy logs data helped to determine the mineralogy of the fillings. The fracture zones had clear responses in the image and sonic data too. The un-filled or half-filled breccia zone were the best zones in the fault-dominated carbonated reservoir. The details of the fault-dominated carbonate reservoir could be used in the future three-dimensional geological modelling.

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.

A Practical Method for the Automatic Recognition of Rock Structures in Panoramic Borehole Image during Deep-Hole Drilling Engineering

Digital panoramic borehole imaging technology has been widely used in the practice of drilling engineering. Based on many high-definition panoramic borehole images obtained by the borehole imaging system, this paper puts forward an automatic recognition method based on clustering and characteristic functions to perform intelligent analysis and automatic interpretation researches, and successfully applied to the analysis of the borehole images obtained at the Wudongde Hydropower Station in the south-west of China. The results show that the automatic recognition method can fully and quickly automatically identify most of the important structural planes and their position, dip, dip angle and gap width and other characteristic parameter information in the entire borehole image. The recognition rate of the main structural plane is about 90%. The accuracy rate is about 85%, the total time cost is about 3 h, and the accuracy deviation is less than 4% among the 12 boreholes with a depth of about 50 m. The application of automatic recognition technology to the panoramic borehole image can greatly improve work efficiency, reduce the time cost, and avoid the interference caused by humans, making it possible to automatically recognize the structural plane parameters of the full-hole image.

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.