# Control Mechanisms for Self-Sealing in Activated Clay-Rich Faults Through Controlled Hydraulic Injection Experiment

Yves Guglielmi, Frédéric Cappa, Jonathan Ajo-Franklin, Florian Soom, Bill Lanyon, Paul Cook, Chet Hopp, Verónica Rodríguez Tribaldos, Michelle Robertson, Todd Wood, et al.

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## To cite this version:

Yves Guglielmi, Frédéric Cappa, Jonathan Ajo-Franklin, Florian Soom, Bill Lanyon, et al., Control Mechanisms for Self-Sealing in Activated Clay-Rich Faults Through Controlled Hydraulic Injection Experiment. Water Resources Research, 2025, 10.1029/2024WR037595. http://hal-05017196

HAL Id: hal-05017196

https://hal.science/hal-05017196v1

Submitted on 2 Apr 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# Water Resources Research®

## RESEARCH ARTICLE

10.1029/2024WR037595

**Key Points:**

* High-pressure injection fault activation experiment at the Mont Terri underground research laboratory

* Continuous transmissivity measurements record self-sealing inside a clay-rich fault zone

* Transmissivity undergoes a phase of domination by slow plastic compaction and shearing during the initial post-activation period, with mineral swelling exerting its influence over the long term

**Correspondence to:**

Y. Guglielmi,
 yguglielmi@lbl.gov

**Citation:**

Guglielmi, Y., Cappa, F., Shadoan, T., Ajo-Franklin, J., Soom, F., Lanyon, B., et al. (2025). Control mechanisms for self-sealing in activated clay-rich faults through controlled hydraulic injection experiment. *Water Resources Research*, *61*, e2024WR037595. https://doi.org/10.1029/2024WR037595

Received 24 MAR 2024
Accepted 3 MAR 2025

**Author Contributions:**

**Conceptualization:** Yves Guglielmi

**Data curation:** Florian Soom, Paul Cook, Chet Hopp, Michelle Robertson, Todd Wood

**Formal analysis:** Yves Guglielmi, Frédéric Cappa, Bill Lanyon, Verónica Rodríguez Tribaldos

**Investigation:** Florian Soom, Paul Cook, Michelle Robertson, Todd Wood, Senecio Schefer

**Methodology:** Yves Guglielmi, Tanner Shadoan, Jonathan Ajo-Franklin, Paul Cook

**Software:** Craig Ulrich, Senecio Schefer

**Supervision:** Yves Guglielmi

**Visualization:** Craig Ulrich

**Writing – original draft:** Yves Guglielmi

**Writing – review & editing:**

Frédéric Cappa, Jonathan Ajo-Franklin, Bill Lanyon, Verónica Rodríguez

© 2025. The Author(s).
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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## Control Mechanisms for Self-Sealing in Activated Clay-Rich Faults Through Controlled Hydraulic Injection Experiment

Yves Guglielmi¹ ID, Frédéric Cappa² ID, Tanner Shadoan³ ID, Jonathan Ajo-Franklin³ ID, Florian Soom¹ ID, Bill Lanyon⁴, Paul Cook¹, Chet Hopp¹ ID, Verónica Rodríguez Tribaldos¹, Michelle Robertson¹, Todd Wood¹, Craig Ulrich¹, Senecio Schefer⁵ ID, Christophe Nussbaum⁵, and Jens Birkholzer¹

¹Energy Geosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA, ²Université Côte d'Azur, CNRS, Observatoire de la Côte d'Azur, IRD, Géoazur, Sophia, Antipolis, France, ³Department of Earth, Environmental, and Planetary Science, Rice University, Houston, TX, USA, ⁴Fracture Systems Ltd, Cornwall, UK, ⁵Federal Office of Topography, Wabern, Switzerland

**Abstract** In a high-pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi-weekly for a year revealed the gradual return of fault transmissivity to its initial state. The study utilized fluid pressure decay analysis, optical fiber monitoring, continuous active source seismic measurements and borehole displacement sensors for measuring fault displacements. The fault zone exhibited a dilation of approximately 1.4 mm, associated with both normal and tangential movements during activation, resulting in a sudden transmissivity increase from $1 \times 10^{-12}$ to $3.2 \times 10^{-7}$ m$^2$/s. Early post-activation, transient compaction and the subsequent slow compaction were observed, transitioning to an extension regime. The pressure pulse tests demonstrated a rapid transmissivity drop by more than two orders of magnitude within the first 10 days, followed by a gradual and less pronounced decrease. Plastic shear and compaction dominated the transmissivity evolution until 70 days after injection ended, followed by a period where additional factors, such as clay mineral swelling, influenced the behavior. Extrapolation suggested a sealing process taking at least 50 years after the initial activation.

**Plain Language Summary** A field-scale fault activation experiment offers valuable insights into the elasto-plastic processes governing the sealing of shale faults. The experiment reveals a rapid increase in the fault's transmissivity by approximately five orders of magnitude during activation. Subsequent observations show a gradual transmissivity decrease by about three orders of magnitude post-activation, with slow long-term plastic shear and compaction of the fault competing against secondary processes, notably clay mineral swelling. All conceptual models employed to interpret these field data converge on the estimation that the fault's return to its initial low transmissivity state would require a minimum of 50 years.

## 1. Introduction

A better understanding of clay-rich fault permeability development during fracturing and sealing periods is important in several ways. For example, the transmissivity evolution of a caprock or host rock fault after being activated by a seismic or aseismic event may control whether a CO₂ storage project or a geological repository for high-level radioactive waste maintain a functioning natural barrier over the long term. Moreover, long-term changes in fault transmissivity may govern the pore pressure evolution during the interseismic phase of an earthquake cycle, and thus drive the eventual occurrence and characteristics of the next seismic event (Gratier, 2011; Xue et al., 2013).

In the case of high-level radioactive waste disposal nested in an argillite layer, repository-induced effects (Leupin et al., 2016) such as the creation of an Excavation Damage Zone (EDZ), gas generation (Nagra, 2008), or thermally induced pore pressure perturbations (Ghabezloo & Sulem, 2009) may result in the activation of pre-existing faults and fractures within the host rock and consequent permeability increase. In underground CO₂ storage, the large-scale fluid pressure changes expected from industrial injections need to be kept lower, by regulation, than the intact rock fracturing pressure to avoid geomechanical damage in the reservoir and hydro-fracturing in the confining caprock units. Nevertheless, these injection pressures may be high enough to activate
Tribaldos, Christophe Nussbaum,
Jens Birkholzer

dilatant shearing on natural pre-existing faults intersecting the reservoir-caprock system (Guglielmi et al., 2021). This could result in the creation of permeable flow pathways along the faults (Pruess, 2005) which could allow for CO₂ to penetrate and migrate through the overlying sealing formations. Unless caprock clay-rich fault self-sealing occurs, the CO₂ could escape from the reservoir, and eventually end up in overlying fresh-water aquifers or leak to the surface, thus creating a risk to the environment and defeating the sequestration purpose.

Workflows based on the fault content in clay minerals and on the fault tendency to slip and dilate allow estimating the risk of fault activation and leakage (Yielding et al., 1997). However, little work has been done to understand and be able to predict how and when clay-rich faults may seal after activation (fault sealing is defined as its hydraulic transmissivity reduction with time). This is particularly important for the moderate activation events of a few millimeters to centimeter of fault slip that are currently calculated from numerical models of fault activation by induced supercritical CO₂ injection at relevant storage depths (see for example, Cappa & Rutqvist, 2011).

At the same time, in laboratory-scale experiments, it has been observed that the sealing of “single” fractures in clay-rich samples may be almost complete. Indeed, at the end of the test, the hydraulic conductivity of the fracture is often like that of the intact rock. In the case of a fracture set in an isotropic state of stress, the main observed sealing mechanisms are twofold: first, hydration enhances the weakening and widening of contact areas between fracture walls, and second, an increase in the confining stress induces closure of the mechanical aperture of the fracture (Bastiaens et al., 2007; Voltolini & Ajo-Franklin, 2020). Shearing of a fracture at effective normal stress higher than the strength of its asperities induces a drastic permeability decrease due to asperity ablation and the formation of gouge. Nevertheless, this process may not lead to complete sealing as the permeability may remain several orders of magnitude higher than the intact rock (Gutierrez et al., 2000). At the field scale in the Mont Terri underground research laboratory (Switzerland), Bossart et al. (2004) reported that the hydraulic conductivity of fractures within the EDZ of a gallery in the Opalinus Clay decreased from $5 \times 10^{-7}$ to $2 \times 10^{-9}$ m/s over the first 3 years following excavation. At this site, fractures were intersected by boreholes sealed with inflatable packer systems and saturated with water for repeated fracture permeability tests. The observed decay in hydraulic conductivity highlighted the significant effect of re-saturation on the partial sealing of fractures. The estimated sealing rate of about $1 \times 10^{-1}$ m/s/year showed that it could take hundreds of years for the fractures of the EDZ to completely close. However, additional tests conducted at the end of this re-saturation experiment showed that increasing stress at the gallery walls strongly decreased the fractures transmissivity (Bastiaens et al., 2007). Additionally, similar field experiments on the sealing of EDZ fractures conducted in other clay rocks, respectively the Callovo-Oxfordian (France) and the Boom clay (Belgium), roughly showed sealing rates of $1 \times 10^{-1}$ to $1 \times 10^{-2}$ m/s/year (Bernier et al., 2004; Delay et al., 2007). Self-sealing occurs at various rates which depend on the site-specific geology such as the type of clay minerals, the degree of mudrock consolidation, and the chemistry of the pore water.

To our knowledge, there are very few direct in-situ experimental measurements of the self-sealing of clay-rich fault zones. Geological observations highlight that self-sealing in faults is potentially favored by a relatively large portion of granular material, mainly made of platy phyllosilicates with a preferential alignment in the direction of the fault (Badertscher et al., 2008; Laurich et al., 2014). At the field scale, clay smear mechanisms and fault zone clay content higher than 20% favor fault sealing (Yielding et al., 1997). Nevertheless, the question that remains poorly understood is how a natural fault that is initially sealed but then opened and sheared by a fault activation event can then recover its low transmissivity through self-sealing effects. In the oil and gas industry, there are numerous reported studies of long-lasting active hydrocarbon fluid flow along faults through caprock formations, apparently a result of active tectonics and deep reservoir overpressures working together to maintain slow fault movements and associated leakage (Mohammedyasin et al., 2016).

Sealing or healing rates have also been studied in periods between large magnitude earthquakes, often referred to as inter-seismic periods. For instance, Doan et al. (2006) conducted hydraulic tests at 1.1 km depth across the seismically active Chelungpu fault zone (affecting shales) 6 years after the 1999 Chichi $M_w$ 7.6 earthquake. They found a permeability of $\sim 1 \times 10^{-16}$ m² for the damaged zone of the fault, which is a factor of 100 higher than the average permeability of the host rock. This permeability change represents a small enhancement compared to other faults where a factor of 1000 in permeability enhancement were measured (Manning & Ingebritsen, 1999; Townsend & Zoback, 2000). A possible explanation of this less pronounced permeability increase is that the recovery of the fault zone is well advanced only 6 years after the Chichi earthquake (Doan et al., 2006). In another study, Ma et al. (2019) used water level response to earth tides and repeated hydraulic slug tests in a well
intersecting the Qujiang fault (China) at about 200 m depth to monitor fault permeability evolution over a 17 year long period from 2001 to 2018, 31 years after the 1970 Tonghai $M_w$ 7.8 earthquake that ruptured the fault. The fault intersects a thick series of clay-rich siltstones and sandstones and is considered tectonically active with a present day 4.5 mm/year dextral strike slip rate (Yu et al., 2020). Although the fault is actively creeping, the permeability is relatively stable with values fluctuating by about 25% around an average permeability of $4 \times 10^{-14} m^2$. In addition, no trend was observed highlighting some ongoing sealing of the fault zone following the Main Tonghai earthquake. In both the Chelungpu and Qujiang studies, the fact that the fault permeability measured after the earthquake remained high may either mean that no sealing occurred or that an incomplete sealing took place over a time scale less than 6–30 years long.

Furthermore, Xue et al. (2013) repeated permeability estimations based on continuous tidal borehole pressure measurements lasting 1 year. These measurements were taken at a depth of 800 m across the main fault zone, 2 years after the slip activation caused by the 2008 Wenchuan (China) $M_w$ 7.9 earthquake. The Wenchuan fault zone is made of complex rocks because it is at the boundary between diorite/porphyrite and siltstone/shales. Conventionally, the tidal approach allows estimating the bulk permeability of a zone of about 40 m radius from the monitoring well, thus integrating over a part of the full fault zone thickness estimated to about 100 m. The fault permeability is quite high, about $1–2 \times 10^{-15} m^2$, and larger than the average intact rock permeability of $1.9 \times 10^{-16} m^2$. This is mainly explained by a dense network of open fractures in the fault damage zone. Over the monitoring period, fault permeability displays a general $4.1 \times 10^{-16} m^2$/year decreasing trend that is attributed to post-Wenchuan earthquake sealing. In detail, the trend shows fast fluctuations that may correspond to episodic fault movements in response to seismic wave loading from remote earthquakes. Moreover, Kitagawa et al. (2013) repeated permeability analyses from borehole injections at 540 m depth in the granitic hanging wall of a fracture damage zone near the Nogima fault zone (Japan). These were done 2 and 5 years after the 1995 Hyogoken-Nanbu $M_w$ 7.3 earthquake that activated the fault. They found a 50% decrease of the permeability within 3 years, corresponding to a permeability decrease rate of about $1 \times 10^{-13} m^2$/year. These two studies highlight a notable trend of rapid permeability reduction over a span of months to a few years following a significant earthquake. In contrast, even in regions characterized by low tectonic activity, persistent factors such as $CO_2$ buoyancy and the overarching effects of relative permeability may contribute to sustained fault leakage, resulting in a lack of clear sealing. This phenomenon can endure for centuries, as evidenced by observations along faults naturally releasing $CO_2$ in the Colorado Plateau (where faults affect siltstone, shales and sandstones; Jung, 2014).

Previous studies have shown that the mechanisms governing fault sealing encompass various processes, including (a) the precipitation of carbonate primarily occurring in the near-surface depths of faults (Patil & McPherson, 2020), (b) the brittle-ductile deformation of faults facilitated by a high clay content exceeding 50% in caprocks (Bock et al., 2010; Rybacki et al., 2016), and (c) alterations in the effective normal stress on faults, influenced by both leakage into shallower formations and changes in fluid properties when $CO_2$ mixes with fault pore water. Nevertheless, a critical gap exists in field-scale data sets, resulting in limited knowledge regarding the relative contributions of these hydromechanical and chemical processes to fault sealing, both in terms of magnitude and over time.

## 1.1. Objectives

In this study, we address the following questions about clay-rich fault permeability development.

1. By how much can the permeability of a clay fault increase when fault shear rupture is nucleated?

2. What are the mechanisms contributing to the self-sealing following the activation of the fault?

3. Can we estimate the time scale for self-sealing of a clay-rich fault from a field scale experimental data set?

## 1.2. A Field Scale Fault Activation Experiment With Permeability Long-Term Monitoring

Here we describe a field experiment conducted in 2020 in the Mont Terri underground research laboratory in Switzerland where a kilometer-scale clay-rich fault was intentionally activated by fluid injection, resulting in the development of a high-permeability leakage flow path. This fault intersects the Opalinus Clay layer, recognized as a suitable host rock/caprock analog. Initially inactive, the fault exhibited a very low permeability ranging from $6 \times 10^{-17}$ to $1 \times 10^{-19} m^2$, closely resembling that of the intact clay rock (Guglielmi et al., 2021). Following the intentional activation of the fault, accompanied by a significant permeability increase, fluid injection was stopped, and the post-activation sealing of the fault was monitored for approximately 1 year. The transient transmissivity
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Fault activation experiment setting. (a) Three-dimensional fault zone view with the different boreholes drilled for monitoring and injection; Black lines are instrumented with Continuous Active-Source Seismic Monitoring sources and receivers. The p-waves velocities image draped on the fault surface corresponds to the end of injection cycle 6 (see Figure 2), and (b) Details of the BFS-B2 injection borehole completion and instrumentation setting (same setting was deployed at BCS-D7).</figcaption></figure>

recovery of the fault was measured with pulse tests that were repeated about every 2–4 weeks. Concurrently, continuous monitoring of fault pore pressure, displacements, distributed strains, and changes in P-wave seismic velocities across the fault provided insights into the mechanisms governing fault sealing. This paper begins by outlining the experimental setup at the field scale. Subsequently, we illustrate how fault deformations during activation and in the year following activation led to a substantial increase in fault transmissivity, followed by an incomplete recovery to the initial transmissivity. To explain our experimental data, we propose a constitutive relationship for the long-term evolution of fault transmissivity, considering the effects of stress relaxation and visco-plastic shearing on fault sealing. Lastly, we discuss how fault visco-plastic mechanisms induced by deep fluid injections may modify the long-term fault sealing capabilities, comparing these findings with other fault sealing relationships reliant on chemically driven healing rates.

## 2. Experimental Setting

The experiment focuses on the hydraulic stimulation of parts of the Main Fault at the Mont Terri underground research laboratory (Switzerland) (Thury & Bossart, 1999) and is performed in a roughly cubic volume of rock with side lengths of 70 m (Figure 1a). The Main Fault zone has strike, dip angle and thickness variations of N040°–N075°, 40°–65° SE and 1–6 m, respectively. The fault zone has a principal shear zone in contact with a 1–2 m thick core of intense clay deformation (“scaly fabric”) (Nussbaum et al., 2011). There is minimal fracture damage zone in the fault hanging wall. In the fault foot wall, the fracture damage zone is about 3–4 m thick. The fault shear offset is ~10 m. At the experiment depth (~340 m), the ambient formation pore pressures are ~0.5–1.2 MPa. The effective normal stress on the fault is about 3.9–4.5 MPa, and the shear stress tangential to the fault is about 0.4–0.9 MPa (Cappa et al., 2022). Given this state of stress, the fault and most of the secondary features contained in the fault zone are not optimally oriented versus stress for shear slip activation. Outside the fault zone,
the Mont Terri tectonic deformations are mostly characterized by a large density of minor faults parallel to bedding with a 2–4 m spacing and a length >10 m (Nussbaum et al., 2011).

The experimental volume includes several boreholes either set outside the fault zone or entirely crosscutting the fault zone (Figure 1a). A feature of the experiment is the extensive geophysical imaging prior, during and after stimulation (Shadoan et al., 2023). The test was monitored in boreholes instrumented with 3D displacement sensors, accelerometers and acoustic sensors, optical fibers (Rodríguez Tribaldos et al., 2023), active seismic sources and receivers, as well as pore pressure (for details on the entire monitoring system, see Guglielmi et al., 2022). In this paper, we focus on measurements conducted at the injection borehole (BFS-B2, Figure 1a) and on P-wave seismic velocity variations measured between a source and a receiver aligned along a seismic ray path crosscutting the fault zone close to the injection borehole.

BFS-B2 is a 146 mm diameter borehole that is oriented at an angle of 52 ± 3° with the fault principal shear surface. It is fully crosscutting the entire fault zone between 39 and 46 m lengths. The total length of the borehole is 55 m. The borehole is Polyvinyl Chloride (PVC) cased except at five 1 m long screened intervals. Two intervals are set across the top and bottom part of the fault zone while the other three intervals are set in the intact rock in the fault foot and hanging walls. The screened sections consist of two stainless steel casings with a PVC filter section in the middle (Figure 1b). The filter screen slot size is 0.3 mm. Except in the screened section, the annulus between the PVC casing and the borehole wall was grouted with a mixture of 82 l water, about 8 kg bentonite and about 60 kg cement. To prevent grout and sand from flowing through the filter screen, a geotextile was wrapped around the slotted parts. In the BFS-B2 borehole, as with all the other experimental boreholes, two optical cables were grouted behind the PVC casing, one cable loop with single mode fibers and one cable loop with multimode fibers (Figure 1b). Both cables are multi-fiber, tight-buffered, aramid-packed, coated with a PVC jacket, and manufactured by Corning. The cable loops were not pre-tensioned during grouting. An Omnisens DITEST VISION 778 Dual temperature and strain unit using the Brillouin Optical Time Domain Analysis (BOTDA; Horiguchi & Tateda, 1989) technique was set to continuously monitor DSS along the single mode borehole fiber. The spatial resolution and spatial sampling are 1.5 and 0.51 m, respectively. A temporal stacking interval of 16 min was utilized, averaging over 3,000 points. Frequency start was 10.6 GHz, frequency stop 10.9 GHz and frequency step 1.0 MH.

The strain signals discussed in the following text refer to strains measured parallel to the BFS-B2 borehole axis. Since this borehole is oriented at a 52 ± 3° angle with the fault, these strains integrate both shear and normal strain to the fault. Inside the PVC casing, a double-packer system was deployed to seal the screened interval located at the top of the fault zone. The interval is 2.4 m long. To better describe the orientation of the fault movements and complement the DSS measurements, the interval contains a three-dimensional displacement sensor (called Step-Rate Injection Method for Fracture In-Situ Properties for SIMFIP) (Guglielmi et al., 2013). This sensor was clamped at two borehole points, here set on each side of the Main Fault principal shear surface, and permanently monitors the relative displacement of one point toward the other one. The distance between the two clamping points was 1.4 m. The clamping points were deployed at the upper and lower limit of the screened section, respectively. A second SIMFIP probe was deployed across the fault in borehole BCS-D7 located about 20 m away from the BFS-B2 injection hole.

In the following text, the three-dimensional SIMFIP displacements are described as tangential and normal dis-
placements to the fault. At BFS-B2, the SIMFIP system was only used for the fault activation period. At the end of
the activation, it was replaced by a single packer set at 38 m length. In this long-term setting, the test interval was
thus longer than in the activation setting, spanning from 38 m down to the bottom of BFS-B2 hole at 55 m and
straddling the entire Main Fault zone. This system remained during the entire year following activation, and it was
used to conduct repeated pulse tests for fault transmissivity monitoring. At BCS-D7, the SIMFIP system remained
in place during the entire activation and post-activation periods.

The cross-well Continuous Active-Source Seismic Monitoring (CASSM) technology was deployed to monitor P- and S-wave seismic velocity changes related to fluid-driven aseismic deformations triggered during the activation of the fault. The CASSM setup includes five dedicated monitoring boreholes (black lines in Figure 1a). Three boreholes have a total of 24 piezoelectric seismic sources (8 each); the other two boreholes have 44 hydrophones in two arrays (22 each). The receiver boreholes are in the foot wall of the fault, while the source boreholes are in the hanging wall. During CASSM acquisition, each source is activated 16 times, while all 44 hydrophones are recording at 48 kHz and stacking to increase signal-to-noise ratio (SNR). The acquisition process cycles through
<figure><img src="image_5.png" /><figcaption>**Figure 2.** (a) to (d) Fluid pressure and flowrate signals at different locations into the fault. Upper graph (a) shows the injection flowrate cycles used to activate the fault, Graph (b) shows the fluid pressure signal at injection (BFS-B2), Graph (c) shows pressure variation at BFS-B1 that was hydraulically connected to injection, Graph (d) shows pressure variation at BCS-D7 that was not hydraulically connected (location of boreholes are in Figure 1a and 2e), and (e) P-wave seismic velocities image at the end of injection cycle 6 (modified from Shadoan et al., 2023). Red arrows show the orientation of fault displacement measured with the Step-Rate Injection Method for Fracture In-Situ Properties probes during and after injection. Although the BCS-D7 point is about 10 m outside the p-wave velocity anomaly, it displays a fault movement that is consistent with the one measured at the injection point.</figcaption></figure>

all sources to generate a single CASSM epoch. The time to complete each full sequence is about 8 min, the temporal resolution of this system. Each CASSM epoch is inverted using a fault-constrained traveltime inversion approach to yield timelapse P-wave velocity difference across the fault plane (Shadoan et al., 2023). The high repeatability of the system allows for characterization of small velocity changes with a temporal precision in the 100s of ns range (Figures 1 and 2); additional results about the CASSM system and fault leakage imaging are found in Shadoan et al. (2023).

The activation experiment was performed as a series of 6 high-pressure injection cycles on 21 November 2020, at constant flowrates of 2 l/min (injection 1), 6 l/min (injection 2), 9.8 l/min (injection 3), 9.94 l/min (injection 4), 9.55 l/min (injection 5) and 10 l/min (injection 6) (Figure 3a). The duration of the first five injections was 10 min each and the sixth was 20 min. The injection interval was shut-in between injection periods. The total time elapsed from the start of injection 1 and completion of injection 6 was 8 hr and 10 min.

## 3. Fault Activation and Post Activation Long Term Hydromechanical Response

The fault hydraulically opened at injection pressures between 5 and 6 MPa. After a total injected volume of 80 L (after cycle 2, Figure 2a), a hydraulic connection occurred across the 1.5 m thick fault zone crosscut by the injection borehole BFS-B2 (this was detected in injection borehole BFS-B2 below the sealed injection interval). After a cumulative injected volume of 178 L (during cycle 3, Figure 2a), another hydraulic connection occurred, characterized by a sudden peak in pressure at borehole BFSB1 intersecting the fault 15–18 m away along strike and NE from the injection point (Figures 2c and 2e). No clear hydraulic connection was observed in borehole BCS-D7 intersecting the fault 8–10 m up-dip and 15–20 m SW along strike from the injection point where a slight pressure decrease was observed (Figures 2d and 2e). These local borehole observations are consistent with time-lapse travel-time tomography obtained from the CASSM measurements, which revealed a zone of decreased P-wave seismic velocity of up to 16 m/s, during each injection (Shadoan et al., 2023, Figures 1a and 2e). These observations show an apparent heterogeneity in the fault leakage that preferentially developed parallel to the fault strike between boreholes BFS-B2 and BFS-B1 (Figure 2e). Borehole BCS-D7 remained outside the leakage zone (Figure 2e). At the end of the injection, outflow at the monitoring borehole BFSB1 was measured to about 26% of
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Fault mechanical response in the near field of injection borehole BFS-B2 and in the far field at BCS-D7. (a) Injected flowrate and fluid pressure, (b) P-wave seismic travel time measured along a ray path crosscutting the fault in borehole BFS-B2 nearfield, (c) Distributed Strains (DSS) strains variations versus time at different depths along BFS-B2, (d) Fault normal and tangential displacements monitored with the Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP) probe at BFS-B2, (e) Fault normal and tangential displacements monitored with the SIMFIP probe at BCS-D7, (f) Maximum DSS strain distributed across the fault zone at the end of the activation experiment (strains are picked at the end of injection cycle 6 along the dashed line indicated on the graphs), and (g) stereographic view of fault displacement at BFS-B2 at the end of injection.</figcaption></figure>

the injected flowrate. The outflow rate stopped and remained quasi steady-state several minutes after the injection stopped.

At the injection borehole nearfield (BFS-B2), there is a reasonably good correlation between fault displacements, DSS, and P-wave seismic travel times delays (Figure 3). There is a 6–15 microseconds increase in the P-waves delay time (Figure 3b) when pressure is increased in the fault during each of the five injection cycles, and when there is a normal opening and a tangential shearing of the fault (Figure 3d). The travel time delays, and the DSS only start significantly varying at the second injection cycle (Figures 3b and 3c). The first injection cycle is not seen because it corresponds to a small 2 L injection volume, and small maximum normal opening and shearing of the fault of 30 and 50 µm, respectively (Figure 3d). Small displacements are related to a relatively low injection pressure of 5.3 MPa. During the first injection cycle, displacements localize in the borehole nearfield, and the small maximum injection pressures may reveal some borehole wall re-saturation effects. Thus, the very local displacements at the borehole wall and their small magnitude might be below the sensitivity of the CASSM and DSS systems. When more water is injected during the following cycles, displacements and strain signatures start spreading along the fault zone and away from the borehole influence. This is when they start being captured by the CASSM and by the DSS monitoring systems.
There is a significant tangential displacement with a reversible component related to the variations in injected pressure and an apparent irreversible and time dependent increasing trend (Figure 3d). During the shut-in periods, delay times partially recover back to background levels before the next injection cycle. This is in good accordance with the partial closure and tangential fault displacement (Figures 3b and 3d). This reversible displacement component is directly proportional to pressure. The irreversible component is associated with shear and normal closure temporal evolution at ambient fault pore pressure. 0.5 days after the last injection and the end of fault-controlled activation experiment, there is a residual delay time of 2–3 microseconds correlated with a residual tangential displacement of 150 µm and a normal over-closure of 80 µm.

The 16 min temporal sampling does not allow the DSS to accurately capture the fault response during the six injection cycles (Figures 3b and 3c). There is a significant irreversible increase in strains that are distributed across the fault zone. At the end of injections, DSS strains show a peak value of ~400 × 10⁻⁶ strain at 40.7 m length in borehole BFS-B2 which is at the location of the top Main Fault principal shear zone (Figure 3f). The strain decreases to values of 100 and 50 × 10⁻⁶ strains toward the bottom of the fault zone at ~56 m length. All DSS strains display an extension (positive strain variation). Integrated over the entire fault zone thickness from 39 to 45 m (Figure 3f), the DSS strains correspond to a fault dilation of about 1400 × 10⁻⁶ m. This value of fault thickness variation is in good accordance with the value estimated from P-wave seismic velocities by Shadoan et al. (2023) using a stress-dependent fracture aperture model. The comparison with fault displacements measured with the SIMFIP probe shows that this dilation is complex, involving both normal and tangential fault movements. The residual displacement vector orientation at the end of injection displays a dip direction and dip angle of 92° and 30° respectively, which highlights a fault activation mechanism in normal faulting with a left lateral strike-slip component (Figure 3g). This movement is in good accordance with the orientation of the regional stress tensor.

At the monitoring hole BCS-D7 which remains outside the pressurized patch, a slow and micrometer scale tangential movement associated to a fault normal closing is triggered after injection cycle 1 (Figure 3e). It is associated to the small fluid pressure drop observed in Figure 2d. At the end of the injection period, the slow movement continues. No reversible response is observed.

The hydromechanical response of the fault was then monitored for about 1 year following activation (Figure 4). At the injection point, fault pore pressure decreased to ambient formation pressure in less than an hour (Figure 4a). The P-wave seismic velocity delay time recovers to its initial value after about 10 days (Figure 4b). During this period, there is a fault contraction characterized by a negative strain variation at 40.7 m (i.e., across the principal shear zone). After 10 days, there is no more pore pressure variation measured at the different monitoring points. Nevertheless, fault contraction continues long after the observed P-wave delay time and pore pressure recovery, until about 70 days after activation end. After 70 days, there is a slight but significant fault dilation. A residual value of about 200 micro-strains is measured after about 200 days (Figure 4b). Although the SIMFIP probe was removed from BFS-B2 for the long-term monitoring, we conclude that the observed contraction corresponds to a tangential and a normal fault displacement component. This is supported by SIMFIP observations at the monitoring hole BCS-D7 that show an irreversible fault tangential movement associated to normal closure lasting until 60–70 days after injection end (Figure 4c). After 70 days, the extension is not associated with any P-wave seismic velocity change and may not relate to a slip induced dilation because there is no clear explanation why slip compaction would switch to slip dilation at this time. This observation could reveal another mechanism related to the swelling of fault clay minerals. Indeed, we hypothesize that, after 70 days, the magnitude of the slip induced compaction process is becoming very small making the effect of mineral swelling observable in the measurements.

# 4. Fault Transmissivity Evolution

## 4.1. Estimation of Fault Transmissivity During Activation

The injection test analyses considered here are focused on the estimation of the SIMFIP interval compressibility in the BFS-B2 injection borehole (Figure 1) and the effective transmissivity of the reactivated feature during the high-pressure injection steps for comparison with the later long-term series of hydraulic pulse tests. The early time pressure responses for the six injection cycles are plotted against pumped volume in Figure 5a. Cycles 1 and 2 show a considerably lower initial slope possibly indicating partial saturation of the interval. From Cycle 3 onwards the early time test response is very consistent with a slope that gives an estimate of the injection interval's compressibility values of 0.8–1 × 10⁻¹⁰ m³/Pa. Steady flow and pressure are observed in BFS-B2 from ~200 s in
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Long term fault hydromechanical response. (a) Flow rate and fluid pressure versus time at BFS-B2, (b) P-wave seismic velocity and Distributed Strains strain measured at 40.7 m versus time at BFS-B2, (c) Tangential and normal fault displacements versus time at BCS-D7, and (d) Estimated values of fault hydraulic transmissivity as a function of time. Drawings 1 to 4 are modified from Fang et al. (2017). Drawings schematically figure the evolution of a rough clay-rich fault under shearing and swelling.</figcaption></figure>

all steps (Figure 5a). Figure 5b shows the injectivity (defined as the ratio of flow rate and hydraulic head) against pumped volume for the different hydraulic stimulation cycles. From Cycle 3 onwards after 1 L of injection the injectivity is remarkably steady and consistent between cycles suggesting that at least locally around the injection borehole relatively constant hydraulic conditions exist. This suggests that it may be possible to use the Thiem equation (Thiem, 1906) to provide a rough estimate of the interval transmissivity local to BFS-B2. Away from the pumping borehole it is likely that there may be ongoing deformation. The Thiem equation assumes steady uniform radial flow where:

$$Q = \frac{2\pi T \Delta h}{\ln(r_{BC}/r_{bh})} \qquad (1)$$

where Q is the volumetric flowrate (m³/s), T is transmissivity (m²/s), Δh is the change in hydraulic head (m), r<sub>BC</sub> is the borehole radius (m), and r<sub>bh</sub> is the radial distance to constant head boundary (m).

While large-scale radial flow in the reactivated feature is unlikely as observed in the P-wave tomography images in Figure 2b, the Thiem equation may be applicable at the local scale around the BFS-B2 injection interval and between BFS-B2 and BFS-B1. The similarity in response to Cycles 4, 5, 6 results in similar values of transmissivity for the region around the injection interval BFS-B2 of ~3 × 10⁻⁷ m²/s (equivalent to a parallel plate
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Hydraulic data measured in the fault. (a) Fluid pressure versus pumped volume during the six injection cycles, (b) Injectivity versus pumped volume during the six injection cycles, (c) Example of a pulse test, and (d) Pulse tests decay curves comparison.</figcaption></figure>

aperture of 73 µm) for the three tests, while the transmissivity around BFS-B1 is somewhat lower at ~5 × 10⁻⁸ m²/s (parallel plate aperture 40 µm). These values are in the range of values calculated using a fully coupled hydromechanical numerical code (Jeanne et al., 2018).

## 4.2. Estimation of Long-Term Fault Transmissivity

A first pulse test was performed on 23 November 2020, 2 days after the fault activation experiments when the SIMFIP tool was still positioned in the BFS-B2 borehole. A pumped volume of 0.315 L was used. After this test, the SIMFIP was removed from the borehole and a single packer was placed in the hole. Pulse 2 (the first pulse test using the single packer configuration) was performed on 25 November 2020 and repeat tests were performed at roughly monthly intervals (Figure 4a). The procedure for each of the 17 repeat tests was identical with an injected volume of 0.5 L. To illustrate a typical test, the measured pressure response in the interval BFS-B2 (single packer) is shown in Figure 5c. Figure 5d shows that the normalized pulse pressure decay curve evolves with time after activation; the decay time increases consistently from earlier to later pulse tests. The HyTool Matlab library (Renard, 2017) was used to analyze the series of long-term pulse tests using the Cooper-Papadopulos (Neuzil, 1982) model. The input parameters were.

* $P_0$ (MPa) the undisturbed pressure, which is estimated from the average measured pressure prior to the pulse.

* $P_I$ (MPa) the peak pressure, which is estimated from the maximum pressure during the pulse.

* $C_w$ (m³/Pa) wellbore compressibility, which is estimated from the pumped volume (0.315 or 0.5 L) and the maximum pressure change ($P_I - P_0$).

* $V_w$ (m³) the test section volume estimated from the borehole radius ($m$) and interval length ($m$).

* $C_{\text{eff}}$ (1/Pa) the effective compressibility, which is calculated from $C_w$ and the test section volume.

The values used for these parameters are listed in Table 1.

The estimated interval compressibility ($1.16 \times 10^{-10}$ m³/Pa) for Pulse 1 using the SIMFIP double-packer tool is ~40% lower than for the later tests where the injection interval is sealed with a single packer and much longer than
<table><caption>**Table 1**
Pulse Tests Parameters Used in the Transmissivity Analyses</caption><thead><tr><th></th><th>C (m³/Pa)</th><th>P₀ (MPa)</th><th>P₁ (MPa)</th><th>ΔP (MPa)</th><th>Pulse volume (l)</th></tr></thead><tbody><tr><td>Pulse 1</td><td>1.16E-10</td><td>0.43</td><td>3.15</td><td>2.72</td><td>0.315</td></tr><tr><td>Pulse 2</td><td>2.18E-10</td><td>0.35</td><td>2.65</td><td>2.29</td><td>0.5</td></tr><tr><td>Pulse 3</td><td>1.84E-10</td><td>0.42</td><td>3.14</td><td>2.72</td><td>0.5</td></tr><tr><td>Pulse 4</td><td>1.58E-10</td><td>0.34</td><td>3.50</td><td>3.16</td><td>0.5</td></tr><tr><td>Pulse 5</td><td>1.52E-10</td><td>0.34</td><td>3.62</td><td>3.28</td><td>0.5</td></tr><tr><td>Pulse 6</td><td>1.60E-10</td><td>0.34</td><td>3.47</td><td>3.13</td><td>0.5</td></tr><tr><td>Pulse 7</td><td>1.68E-10</td><td>0.34</td><td>3.32</td><td>2.98</td><td>0.5</td></tr><tr><td>Pulse 8</td><td>1.56E-10</td><td>0.34</td><td>3.55</td><td>3.21</td><td>0.5</td></tr><tr><td>Pulse 9</td><td>1.62E-10</td><td>0.35</td><td>3.43</td><td>3.08</td><td>0.5</td></tr><tr><td>Pulse 10</td><td>1.65E-10</td><td>0.35</td><td>3.38</td><td>3.03</td><td>0.5</td></tr><tr><td>Pulse 11</td><td>1.63E-10</td><td>0.35</td><td>3.41</td><td>3.07</td><td>0.5</td></tr><tr><td>Pulse 12</td><td>1.63E-10</td><td>0.35</td><td>3.42</td><td>3.07</td><td>0.5</td></tr><tr><td>Pulse 13</td><td>1.58E-10</td><td>0.36</td><td>3.53</td><td>3.17</td><td>0.5</td></tr><tr><td>Pulse 14</td><td>1.70E-10</td><td>0.37</td><td>3.32</td><td>2.94</td><td>0.5</td></tr><tr><td>Pulse 15</td><td>2.04E-10</td><td>0.39</td><td>2.83</td><td>2.45</td><td>0.5</td></tr><tr><td>Pulse 16<sup>a</sup></td><td>2.66E-10</td><td>0.39</td><td>2.27</td><td>1.88</td><td>&lt;0.5</td></tr><tr><td>Pulse 17</td><td>1.68E-10</td><td>0.38</td><td>3.36</td><td>2.98</td><td>0.5</td></tr></tbody></table>

for Pulse 1. The value is consistent with the compressibility estimates from the high-pressure injections and reflects the shorter interval and difference in packer stiffness between the SIMFIP tool (Pulse 1) and single packer completion (Pulse 2 onwards). The estimated compressibility is consistent from Pulse 3 onwards. The higher compressibility estimated for Pulse 2 may correspond to either some partial saturation or lower injection volume.

The fault storage and transmissivity estimate for both the full and late time (fluid pressure <2.5 MPa) analyses are summarized in Table 2 and plotted in Figure 4d. The storage estimates do not change between the two analyses and show only small variability across the different pulse tests from 1.1 to 2.1 × 10⁻⁶ with a mean value of 1.6 × 10⁻⁶. The analysis of pressure pulse tests shows a fast drop in transmissivity from 3.2 × 10⁻⁷ m²/s during the high-pressure activation phase to 1.8 × 10⁻⁹ m²/s 5 days after activation (Figure 4d). Then, there is a slow decrease of ~1.6 × 10⁻⁹ m²/s per year during the following 8 months. 200 days after activation, the fault transmissivity remains about two orders of magnitude higher than the initial transmissivity before activation.

The pulse test analyses will estimate hydraulic parameters over a relatively small area due to the small injection volume and therefore represent properties local to the injection borehole. At larger scales, as the fracture closes and roughness and tortuosity effects become more important it is likely that the effective transmissivity of the fault will reduce more quickly as the open flow channels (macroporosity) become increasingly disconnected.

<table><caption>**Table 2**
Transmissivity and Storativity Values Estimated From Pulse Tests</caption><thead><tr><th rowspan="2">Test</th><th rowspan="2">Date</th><th rowspan="2">Elapsed days</th><th colspan="2">All data</th><th colspan="2">Late time P &lt; 2.5 MPa</th></tr><tr><th>T (m²/s)</th><th>S (l/m)</th><th>T (m²/s)</th><th>S (l/m)</th></tr></thead><tbody><tr><td>Pulse 1</td><td>23/11/20</td><td>1.8</td><td>5.8 E × 10<sup>-9</sup></td><td></td><td>4.8 × 10<sup>-9</sup></td><td>1.1 × 10<sup>-6</sup></td></tr><tr><td>Pulse 2</td><td>25/11/20</td><td>4.2</td><td>1.1 × 10<sup>-9</sup></td><td></td><td>1.3 × 10<sup>-9</sup></td><td>2.1 × 10<sup>-6</sup></td></tr><tr><td>Pulse 3</td><td>26/11/20</td><td>5.0</td><td>1.8 × 10<sup>-9</sup></td><td></td><td>2.1 × 10<sup>-9</sup></td><td>1.8 × 10<sup>-6</sup></td></tr><tr><td>Pulse 4</td><td>15/12/20</td><td>24</td><td>1.7 × 10<sup>-9</sup></td><td></td><td>1.4 × 10<sup>-9</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 5</td><td>11/01/21</td><td>51</td><td>1.4 × 10<sup>-9</sup></td><td></td><td>1.1 × 10<sup>-9</sup></td><td>1.5 × 10<sup>-6</sup></td></tr><tr><td>Pulse 6</td><td>01/03/21</td><td>100</td><td>1.4 × 10<sup>-9</sup></td><td></td><td>1.1 × 10<sup>-9</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 7</td><td>15/03/21</td><td>114</td><td>1.4 × 10<sup>-9</sup></td><td></td><td>1.1 × 10<sup>-9</sup></td><td>1.7 × 10<sup>-6</sup></td></tr><tr><td>Pulse 8</td><td>29/03/21</td><td>128</td><td>1.3 × 10<sup>-9</sup></td><td></td><td>9.2 × 10<sup>-10</sup></td><td>1.5 × 10<sup>-6</sup></td></tr><tr><td>Pulse 9</td><td>12/04/21</td><td>142</td><td>1.3 × 10<sup>-9</sup></td><td></td><td>9.6 × 10<sup>-10</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 10</td><td>26/04/21</td><td>156</td><td>1.2 × 10<sup>-9</sup></td><td></td><td>8.9 × 10<sup>-10</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 11</td><td>10/05/21</td><td>170</td><td>1.1 × 10<sup>-9</sup></td><td></td><td>5.1 × 10<sup>-10</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 12</td><td>25/05/21</td><td>185</td><td>9.4 × 10<sup>-10</sup></td><td></td><td>7.4 × 10<sup>-10</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 13</td><td>08/06/21</td><td>199</td><td>9.2 × 10<sup>-10</sup></td><td></td><td>4.9 × 10<sup>-10</sup></td><td>1.6 × 10<sup>-6</sup></td></tr><tr><td>Pulse 14</td><td>23/08/21</td><td>275</td><td>5.7 × 10<sup>-10</sup></td><td></td><td>3.4 × 10<sup>-10</sup></td><td>1.7 × 10<sup>-6</sup></td></tr><tr><td>Pulse 15</td><td>14/09/21</td><td>297</td><td>5.2 × 10<sup>-10</sup></td><td></td><td>3.1 × 10<sup>-10</sup></td><td>1.7 × 10<sup>-6</sup></td></tr><tr><td>Pulse 16<sup>a</sup></td><td>19/10/21</td><td>332</td><td>2.8 × 10<sup>-10</sup></td><td></td><td>2.5 × 10<sup>-10</sup></td><td>1.7 × 10<sup>-6</sup></td></tr><tr><td>Pulse 17</td><td>05/11/21</td><td>349</td><td>4.1 × 10<sup>-10</sup></td><td></td><td>2.5 × 10<sup>-10</sup></td><td>1.7 × 10<sup>-6</sup></td></tr></tbody></table>

<footnote>ªPulse 16: pulse volume potentially less than 0.5 L.</footnote>

<footnote>ªPulse 16: uncertain pulse volume see Table 1.</footnote>
## 4.3. Toward a Long-Term Constitutive Relationship for Fault Sealing

### 4.3.1. Fault Transmissivity Dependency on Viscous Strains

The experimental data indicates that the evolution of fault transmissivity is time dependent (Figure 4). For the first 70 days following activation, the decrease in transmissivity correlates in time and with the slow tangential movement and compaction of the fault. From 70 to 120 days, the values of transmissivity do not vary much. After 130 days, there is an acceleration of transmissivity reduction and a slight fault dilation captured by the strain measurements while no P-wave travel time variation is measured.

After 70 days, changes in fault hydraulic transmissivity either occur below the sensitivity of active seismic techniques or the technique is not sensitive to the observed fault dilation. Figure 3 shows that the $50 \times 10^{-6}$ m fault displacements measured with the SIMFIP sensor during injection cycle 1 were hardly detected in both the seismic and DSS data (compare cycle 1 SIMFIP displacements in Figure 3d with P-wave seismic variations Figures 3b and 3c). After 70 days, the dilation is of about $50 \times 10^{-6}$ m and thus it is close to the sensitivity limits of these methods. Nevertheless, it is striking that the measured dilation is followed by a fault hydraulic transmissivity decrease that accelerates when the dilation becomes more significant after about 130 days. This observation indicates that the mechanism that produces dilation does not favor hydraulic connections between fault pores. This is why we hypothesize that dilation may not be associated with the creation of interconnected macroporosity and may not even be associated with porosity creation. The other process causing dilation could then be the swelling of fault clay minerals. Since the effect of swelling may be smaller than the effect of slow slip compaction, it may explain why it is only observed long after the end of activation when the magnitude of slip compaction became very small. Moreover, at about 200 days, the fault transmissivity of $1.1 \times 10^{-9}$ m²/s is still two orders of magnitude higher than the initial pre-activation value estimated to $1 \times 10^{-12}$ m²/s. This residual transmissivity is associated with a residual strain of about 200 µstrains that, as mentioned before, mainly resulted from a compacting shear of the fault that lasted at least 70 days after the end of fault activation.

In summary, these long-term observations suggest that fault transmissivity decreases with time, potentially resulting from three successive processes.

* An initial fast closure of the fault due to the injection pressure drop after injection stop. Closure is related to the increase in effective normal stress. This effect occurs less than 1 hour after the end of injection. This explains the first two orders of magnitude of fault transmissivity decrease.

* A slow $\sim 3.2 \times 10^{-11}$ m²/s per day of transmissivity decrease associated with an average $1.6 \times 10^{-11}$ s⁻¹ strain rate. Such strain rate corresponds to slow compaction associated with irreversible shearing of the fault that lasts until at least 70 days after fault activation.

* A significant acceleration of fault transmissivity decay with time occurring after 130 days. This acceleration correlates with a fault dilation that could be attributed to a dominant effect of clay minerals swelling in the fault, while, at this time, macro-fractures within the fault zone have closed or disconnected.

### 4.3.2. Time Evolution of Fault Transmissivity

Our experimental data indicate that the slow slip and compaction of fault material play a role in the temporal closure of fault flow paths, leading to the observed long-term reduction in transmissivity. In our transmissivity data modeling, we assess two distinct long-term transmissivity evolutions by drawing parallels with generic creep laws commonly employed to characterize the long-term deformation of clay rocks.

The first transmissivity law is expressed through a simple power law governing fault transmissivity (T), defined as:

$$T = T_{\text{initial}} \alpha t^{-n} \qquad (2)$$

This formulation is inspired from a steady state creep law, as detailed in works by Zhang et al., 2007 Gratier et al., 2014; Im et al., 2018.

The second transmissivity law draws inspiration from the creep law applied to uniaxially loaded samples, as outlined by Bock (2009). The reduction in fault hydraulic aperture following injection-induced fault activation is time-dependent and can be described by the following function:
$$b = b_{\min} + (b_{\max} - b_{\min}) \exp(-\alpha t^n) + \left(b_{\min} + \frac{b_{\max} - b_{\min}}{\beta}\right) t^{-p} \quad (3)$$

The first term denotes an immediate (“elastic”) fault opening. The second term, represented as an exponential of time, corresponds to a primary consolidation term, specifically associated with transient primary creep. The third term, expressed as a power law, aligns with secondary consolidation, indicative of steady-state creep.

In both formulations, the transmissivity (T) is subsequently linked to variations in the hydraulic aperture of the fault, according to the relationship:

$$T = \frac{\rho g b^3}{12 \nu} \quad (4)$$

In these three equations, the parameters correspond to:

b = hydraulic aperture (m),

bmin = minimum hydraulic aperture (m),

bmax = maximum hydraulic aperture (m),

α and β = constant (–),

n and p = power exponent (–),

t = time (day),

T = transmissivity (m²/s),

ρ = fluid density (kg/m³),

g = gravity acceleration (m/s²),

ν = fluid dynamic viscosity (Pa.s).

Equations 2–4 delineate the forward models elucidating the decay in fault hydraulic aperture and transmissivity over time. Although treating the fault as a straightforward planar interface with a changing hydraulic aperture constitutes a substantial simplification of reality, our field measurements affirm that strains are predominantly localized along the fault's principal shear surface (refer to Figure 3f).

For the modeling of the fault transmissivity evolution with Equations 2–4, the comparison between observed and calculated transmissivity values is treated as an inverse problem consisting in the determination of optimal values for five independent parameters (including bmin, α, β, n, p), aiming to obtain a calculated evolution of fault transmissivity that best explains the experimental data.

The inverse problem was tackled using a simulated annealing algorithm (Kirkpatrick et al., 1983), which explored 5.3 million solutions in our study for the determination of each free model parameters in Equations 2–4. This algorithm is a stochastic optimization method inspired by metallurgical annealing, a process where metals are heated to high temperatures and then slowly cooled to enhance their structural integrity and reduce defects (Kirkpatrick et al., 1983). This method is highly effective for approximating solutions to intricate optimization problems, particularly those characterized by expansive search spaces or numerous local optima. It efficiently explores the solution space by initially conducting a broad random search to locate the global minimum of the misfit function, thus avoiding local minima. As iterations progress, the exploration narrows down to regions that best fit the experimental data. Central to the algorithm is the theoretical concept of temperature variation, where temperature systematically decreases throughout the inversion process. Starting with a high temperature, the algorithm progressively reduces it in a linear fashion at each step.

In simulated annealing, the acceptance probability follows the Metropolis criterion (Metropolis et al., 1953), which dictates the probability of accepting a worse solution compared to the current solution. The acceptance and retention procedure enhances the algorithm's effectiveness in exploring the search space by facilitating escape from local optima, ultimately leading to convergence toward a global optimum or a near-optimal solution. The gradual decrease in temperature ensures that the algorithm becomes more discerning over time, accepting only improved solutions as it converges. According to the Metropolis criterion, simulated annealing has a certain probability of escaping local minima, and the probability decreases as the temperature decreases, with the optimal solution gradually converging.
<figure><img src="image_9.png" /><figcaption>**Figure 6.** (a) Evolution of predicted fault transmissivity over time compared to experimental data estimated from the series of pulse tests (blue dots with error bars taken at ±20% to take into account possible uncertainty of measurements). Gray lines are obtained for 100 inversions with the first transmissivity law (Equation 2 coupled with Equation 4; Power law (1)), while the orange lines correspond to 100 inversions with the second transmissivity law (Equation 3 coupled with Equation 4; Creep law (2)). The red dashed line represents the mean solution among the 100 best-fit solutions for each law, and (b) Extrapolation of fault transmissivity evolution until “full” recovery to pre-activation value of ~10⁻¹² m²/s.</figcaption></figure>

Simulated annealing has been previously employed in various hydrogeological studies, including groundwater management strategies (Dougherty & Maryott, 1991), fluid flow in fracture systems (Davey Mauldon et al., 1993), and the estimation of permeability in fractured reservoirs (Abdelazim & Rahman, 2016).

Following this, the inversion procedure of the direct model was performed for different random sets of initial values for the two free parameters (α and n) in Equation 2 and the five free parameters ($b_{min}$, α, β, n, p) in Equation 3. The bounds on the prior distribution are given by $1 \times 10^{-6} m < b_{min} < 20 \times 10^{-6} m$, and $0 < \alpha, \beta, n, p < 5$. In Equation 3, the value of $b_{max}$ (73.15 × 10⁻⁶ m) is fixed relative to the maximum measured transmissivity resulting from fault activation by fluid injection (Figures 4c and 6). The misfit function to estimate the difference between the observations and predictions is the reduced chi-square ($\chi^2_r$):

$$ \chi^2_r = \frac{1}{N} \sum_{i=1,N} \left( \frac{obs_i - pred_i}{\sigma_i} \right)^2 \qquad (5) $$

where N is the number of observations (i.e., 18) minus the number of free model parameters (i.e., 2 in Equations 2 and 5 in Equation 3), and $\sigma_i$ is the uncertainties (here, we consider 20% for measurement and model).
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Variations of the two free model parameters (black dots) inverted for the 100 best-fit solutions ($\alpha$ and $n$) as a function of the reduced chi-square for the first transmissivity law (Equation 2 coupled with Equation 4). The red square represents the mean solution of the 100 values for each parameter, and its bars indicate the associated standard deviation.</figcaption></figure>

We conducted the inversion 100 times for each transmissivity law, corresponding to a total of 200 simulations performed in our study. Specifically, we tested Equation 2 and Equation 3 each 100 times. The outcomes indicate that both equations produce nearly identical results across the 100 simulations, thus confirming a high degree of confidence in the accuracy of the models.

We quantify the uncertainty by considering a range of solutions. In inverse modeling method which typically yields a single solution, parameter values are determined and uncertainty in the model is expressed through assigned variances to these parameters. This single solution can be viewed as representing a set of solutions where parameter values lie within likely ranges indicated by the size of the variance.

The scatter plots in Figures 7 and 8 depict the optimal parameters used to fit Equations 2 and 3 to the experimental data. Our approach involves analyzing 100 solutions per equation, ensuring robust estimation of uncertainties associated with each free model parameter. From these 100 solutions for each parameter, accurate estimates of the mean value and associated standard deviation are derived, effectively constraining the range of variations around the mean value for each parameter.

We evaluated the models' capability to accurately predict fault permeability by restricting the data range used to estimate the optimal model parameters to the first 14 measured values (i.e., 78% of the data). Subsequently, we applied forecasts based on these best-fitting physical parameters to predict the last four experimental values (i.e., 22% of the data). This approach enables a precise validation of model parameter estimation.

Figure 6a illustrates the recovery of transmissivity following fault activation induced by fluid injection. Results from 200 inversions show that the second transmissivity law (Equation 3) provides a satisfactory fit to the transmissivity evolution, reasonably matching the observed trends up to approximately 130 days after the
<figure><img src="image_11.png" /><figcaption>**Figure 8.** Variations of the 5 model parameters (black dots) inverted for the 100 best-fit solutions ($b_{min}$, $\alpha$, $\beta$, $n$, $p$) as a function of the reduced chi-square for the second transmissivity law (Equation 3 coupled with Equation 4). The red square represents the mean solution of the 100 values for each parameter, and its bars indicate the associated standard deviation.</figcaption></figure>

cessation of activation. The best-fit estimates of model parameters include a minimum hydraulic aperture ($b_{min}$) of 10.17 × 10⁻⁶ m (±0.17 × 10⁻⁶ m), $\alpha$ of 1.069 (±0.17), $\beta$ of 1.95 (±0.19), $n$ of 1.4 (±0.35), and $p$ of 0.92 (±0.23) (Figure 8). The obtained value of minimum hydraulic aperture is consistent with previous studies which estimated $b_{min}$ at 10 × 10⁻⁶ m (Cappa et al., 2022; Guglielmi et al., 2020).

The first transmissivity law inadequately captures the abrupt decay in the weeks following fault activation, yet it exhibits a better fit to the data beyond the 130 day mark. The best-fit estimates of the two model parameters in Equation 2 include an $\alpha$ of 0.8076 (±4.5 × 10⁻⁴) and $n$ of 1.1 (±5.18 × 10⁻⁷).

Notably, the values of parameters $\alpha$ and $n$ in the first and second laws are approximately identical, indicating that the delayed transmissivity decrease may be attributed to a secondary consolidation. However, as discussed in Section 4.3.1, this consolidation does not align with the minor fault dilation observed. Furthermore, the inability of either law to fully explain the entire data set suggests that the evolution of fault sealing results from a combination of distinct processes.

# 5. Discussion

## 5.1. Initial Fault Permeability - Comparison With Other Measurements

There is a significant evidence-base supporting the overall low-permeability of the undisturbed Opalinus Clay with very low values of ~1 × 10⁻¹⁹ to 1 × 10⁻²¹ m² (Gautschi, 2017). Some previous estimates of permeability of the Main Fault done through injection tests in borehole CSD-7 zone (Figure 1) range from ~1 × 10⁻²⁰ to
~1 × 10⁻²¹ m², and thus show no significant difference with intact rock values (Zappone et al., 2021). Nevertheless, permeability tests performed in boreholes drilled across the Main Fault but from another Mont Terri gallery displayed higher permeability values of 1 × 10⁻¹⁷ to 1 × 10⁻¹⁹ m² (Jeanne et al., 2018; Kneuker et al., 2017). These values are in the range of Opalinus Clay Fractures ones obtained at laboratory scales on samples of various fracture intensity and under the same state of stress (Zhang & Talandier, 2023). Moreover, these initial permeability values are in the range of values for fault zone materials that contain more than 20%–30% of clay materials (Farrell et al., 2021).

If these values are representative of initial fault permeability in the BFS-B2 interval, the stimulated feature has not yet fully self-sealed after 1 year, even though there has been a significant reduction in permeability following activation. An alternative approach to estimation of the permeability of the fault is to consider permeability-porosity relationships for remolded samples (Favero & Laloui, 2018). It shows the porosity range for fault gouges together with the permeability of remolded samples versus void ratio. A porosity range of 16%–22% is equivalent to 0.19–0.28 void ratio. This suggests that the undisturbed permeability of fault rocks, assuming no significant fracture permeability, will be ~1 × 10⁻¹⁹ m². Orellana et al. (2022) conducted the same laboratory approach as Favero and Laloui (2018) on fault zone samples taken from a continuous coring of the fault done in borehole BFS-2 (Figure 1). They highlight that a more permeable fault gouge exists within the low permeability fault zone, located along the Main Fault principal shear zone. Moreover, Orellana et al. (2022) estimate the permeability of this zone to be ~1 × 10⁻¹⁸ m² indicating that the stimulated feature in our experiment is probably still significantly more permeable than in the undisturbed state.

## 5.2. Compaction Associated With Shearing and Swelling as Potential Sealing Mechanisms

Our fault activation experiment mainly produced an aseismic fault slip (with a rate of few microns per second) and sparse seismicity that was mainly caused by local stress perturbations induced around the aseismic slip patch (De Barros et al., 2023). Aseismic slip was triggered by water injection lowering the effective normal stress on the fault. Furthermore, Cappa et al. (2022) showed that the five-orders-of-magnitude fault transmissivity increase upon activation could be associated with drastic fault softening characterized by a rapid drop of the friction coefficient from 0.6 to 0.1. This was confirmed by Shadoan et al. (2023) who interpreted the changes in P-wave seismic velocities traveling through the activated fault patch as related to changes in fault zone thickness caused by perturbations of the fault elastic properties.

The experimental procedure ends the fault activation phase by abruptly stopping water injection into the fault zone. As discussed earlier, this is followed by an early transient slow deformation period of about 10 days progressively transitioning into a ~1.6 × 10⁻¹¹ s⁻¹ quasi-steady-state strain rate measured during the first 70 days following the end of the fault activation. During this 70 day period, contraction strain oblique to the fault is measured while all monitored pore pressures have recovered to pre-activation values. Observations several meters outside the flow patch show that this contraction strain corresponds to irreversible slow shearing associated with closing of the fault. This ~1.6 × 10⁻¹¹ s⁻¹ value is in the range of steady-state creep values measured in the laboratory on Opalinus Clay samples under similar effective deviatoric stress conditions of 1–2 MPa (Zhang & Laurich, 2020). In these laboratory scale experiments, a quasi-steady-state creep is observed after a transient creep phase, caused by the sudden increase in deviatoric stress imposed to the sample. Nevertheless, the comparison with these laboratory measurements must be taken with caution since they are done on partially saturated (S_w of 85%–99%) initially intact rock samples while our field measurements are done in a fully saturated fault zone.

In the field, the slow post-activation fault deformation is driven by both the sudden drop in fault pore pressure and the consequent increase in the effective normal stress, and the mechanical closing of the fault associated with increasing shear stress. Slow deformation is maintained for at least 70 days after injection ends. This process is associated with a two-orders-of-magnitude fault transmissivity decrease that highlights that fluid flow paths may disconnect inside the fault zone. The main mechanism is fault compaction under slow slip which is characterized by fault over-closing starting between the injection cycles and lasting days after the activation experiment (Figure 3d). This could result from complex viscoelastic and viscoplastic response of such clay fault zone. Zhang and Laurich (2020) observed at laboratory scale that the compaction of a wetted sample is about twice larger than the one of a dried sample, and that it lasts several days longer.

At the same time, Orellana (2018) highlighted that saturated clay fault gouges had a much smaller and slower healing rate compared to dry gouges. He suggested that water filling the gouge pores may experience overpressure
due to compaction of the low permeability material. Voltolini and Ajo-Franklin (2020) highlight the effects of hydration of newly damaged fracture asperities that tend to contact and create “choke” points limiting flow between the fracture surface. This has the main consequence of increasing fracture flow tortuosity while little change in the fracture aperture is observed at the scale of their laboratory experiment. They also highlight the strong influence of the increase in the confining stress that almost completely closed the experimental fracture. In our experiment, it appears that most of the observed compaction is localized on the principal shear zone at the top main fault boundary. Indeed, Figures 3 and 4 show that most of the DSS contraction is at 40.7 m (principal shear zone) slowly decreasing with time to the residual value of 200 micro-strain close to the residual value measured in the other fault zone locations. This shows that at the fault zone scale the “localized” compaction along the principal shear zone may maintain “overpressure” within the surrounding fault zone volume. We suggest that it favors the long-term fault deformation and maintains the low-to-zero fault healing.

There are few other observations of the effects of long-term deformation on fault sealing. Most of them are in active tectonics environments where long-term deformation is associated to creep rates that are maintained by tectonic stress. Saffer (2014) conducted a wide range of direct and indirect permeability observations in Ocean Drilling Project (ODP) boreholes cross cutting active faults in different subduction zones where displacement rates are around 7–9 cm/year. The conceptual model is that high permeability (1 × 10⁻¹³ to 1 × 10⁻¹¹ m²) flow paths create in small fraction of the fault surface and spatially migrate or destroy with fault permanent displacements. Over the long term, the average fault zone permeability stays high (around 1 × 10⁻¹⁶ to 1 × 10⁻¹⁴ m²) with several orders of magnitude higher than the intact sediment. Other observations made by Barbour (2015) indicated that the pore pressures response to dynamic strains induced by remote earthquakes in the 100–200 m deep boreholes of the Plate Boundary Observatory network depend nonlinearly on the inverse distance perpendicular to actively creeping faults in California. Although there is no fault permeability estimation in this study, Barbour concludes that tectonic creep rates of 1–3 cm/year generate fault zone dilation and associated permeability increase that dissipates pressure. This is caused by dilatant shear on multiple fractures inside the fault zone. Schematically, this may happen as soon as the fault creep rate is higher than the sealing rate although other factors related to fault structure and mineral content may also matter.

## 5.3. Swelling Effects of Clay Minerals on Fault Sealing

Section 5 shows that it is difficult to model the fault transmissivity reduction with one constitutive law because the fault sealing process includes several competing mechanisms. If the first 70 days after fault activation seem to be dominated by compaction shear and an increase in the effective normal stress, we observe that after 130 days some unexpected fault expansion occurs associated with an acceleration of transmissivity decrease. This is in good accordance with laboratory observations of wetted clay samples where gradual expansion during long term creep experiments is attributed to swelling of clay minerals (Zhang & Laurich, 2020), and it has been documented under confining effective stresses of about 8–9 MPa, thus close to our experiment's stresses (Zhang, 2017a, 2017b; Armand et al., 2014). In these laboratory experiments, the mechanism is that compaction creep reduces distances between clay particles inducing connections between local swelling pressures. These pressures thus apply on interparticle surfaces large enough for the swelling pressures to exceed the external stresses applied on the sample, resulting in the sample's expansion. Zhang. (2017a, 2017b) estimated that swelling pressures in the Opalinus Clay can be as high as ~6 MPa. In our fault experiment, we suggest that after 70 days the creep-induced compaction has led to a similar process as observed at laboratory scale. Given that the effective normal stress on the fault zone is 3.9–4.5 MPa (Guglielmi et al., 2021), it is reasonable to think that a fraction of this swelling pressure would be enough to explain the observed fault expansion after 70 days. Following the reasoning of Section 6.2, it may occur in the volume of the fault zone. This could also explain the slight acceleration of transmissivity decrease after 130 days. The local swelling of clay minerals may create “choke” point within fault zone fractures inducing an overall increase in tortuosity and an associated transmissivity decrease. Nevertheless, the explanation of swelling remains very qualitative with little support of field or laboratory data. We may furthermore consider that the reactivity of the pore fluid with the rock matrix is also temperature and pressure dependent. Both parameters, especially pressure, since the fluid temperature change was less than 5°, would change during the injection, potentially causing enhanced chemical interaction.
## 5.4. Can Complete Fault Sealing Occur?

At the end of our post fault activation monitoring period of ~200 days, a residual fault transmissivity remains. It is about two orders of magnitude higher than the fault transmissivity before activation (considered equal to ~10⁻¹² m²/s in Figure 4c). The time-dependent transmissivity Law 1, $T = T_{initial} \alpha t^{-n}$, with best fit parameters $\alpha = 1.048$, $n = 1.126$ and $T_{initial} = 3.2 \times 10^{-7}$ m²/s (Equation 2), predicts about 50 years for the fault transmissivity to decrease to its pre-activation value of 10⁻¹² m²/s (Figure 6b). In contrast, Law 2, $b = b_{min} + (b_{max} - b_{min}) \exp(-\alpha t^n) + (b_{min} + \frac{b_{max} - b_{min}}{\beta}) \tau^{-p}$, with best fit parameters $b_{min} = 10.17 \times 10^{-6}$ m, $\alpha = 1.069$, $\beta = 1.95$, $n = 1.4$, $p = 0.92$ and the cubic law (Equations 3 and 4), agrees well with the short-term transmissivity drop but then flattens out and may never approach the fault pre-activation transmissivity. Given our data, the Law 1 estimate of 50 years may be more reliable in a non-active tectonic context where fault creep is minimum. Law 2 might need to be considered in other cases. Law 2 may show that if there is some fault creep or slow slipping the fault may never recover its full pre-activation transmissivity.

Whether other mechanisms than clay swelling enhance the transmissivity decrease over the very long term is an open question. The effects of the complex fault zone architecture which contains low indurated scaly clay lenses intercalated with moderate-to-high indurated fractured lenses may also introduce some variability in these estimated sealing times. It is recognized that the self-sealing process depends on the type of clay minerals, the degree of induration, and the chemistry of the fluid (Bock et al., 2010; Crawford et al., 2008). For instance, Bourg (2015) highlighted a correlation between the clay mineral mass fraction $X_{clay}$ and the unconfined compressive strength from a compilation of laboratory experimental data of shales and mudstone rocks. A sharp threshold at $X_{clay} \sim 1/3$ separates sealing shales from brittle shales. Looking at measured EDZ evolution in clay galleries and at natural analogs, Bock et al. (2010) estimate that less indurated argillaceous rocks self-seal in a few months while it takes several years for highly indurated (i.e., highly brittle) argillaceous rocks to seal. From laboratory scale Opalinus clay fractures self-sealing experiments, Zhang and Talandier (2023) suggest that a complete sealing of fractures of a gallery EDZ should occur after tens of thousands of years. Rybacki et al. (2016) made similar observations on the evolution of hydraulic fractures in deep oil and gas boreholes, suggesting that shales with high brittleness tend to slowly close hydraulically created fractures. In a review paper, Neuzil (2019) reports clay-rick fault zones episodes of two to three orders of magnitude permeability changes that last hundreds-to-thousands of years in active tectonics margins.

Moreover, the chemical fluid-rock interactions on sealing can be described with the so-called kinematic permeability, in which the permeability decrease with time can be expressed in Equation 6 as a function of the distance from the fault core (x), the depth (z) and the characteristic decay time ($\tau(z)$) (Gratier et al., 2003):

$$K(x, z, t) = \left(\frac{k_0}{\rho g}\right) e^{-x/L} e^{-3t/\tau(z)} \quad (6)$$

where $\rho$ is the fluid density, $g$ is the gravity, $k_0$ is an initial value, for example, before fault activation, $L$ is the half fault thickness. The characteristic decay time ($\tau(z)$) depends on the crustal depth because it is associated with different rates of fault material compaction. For example, Gratier et al. (2003) assumed the predominance of calcite rate in sealing in the low-temperature and low-pressure upper crust while they assume that quartzite sealing rate dominates at higher temperature and pressure. The depth transition is considered at about 3 km. In Equation 6, the permeability decrease is associated with pressure-solution processes occurring at grain scale in the fault. When fitting Equation 6 on permeability data from the San Andreas fault system, Gratier et al. (2003) get large decay times ranging from 70 to >200 years depending on the initial fault permeability. Note that these are decay times in the same ranges as the ones that are estimated from our experimental data. Nevertheless, it is important to specify that in our fault activation experiment we injected water in chemical equilibrium with the fault rocks. Thus, our results should not be sensitive to fluid-rock chemical interactions as described by Gratier et al. (2003).

Furthermore, in the study of the Wenchuan earthquake fault zone, Xue et al. (2013) finds that the sealing of this fault is relatively fast, corresponding to an exponential decay time of 0.6–2.5 years. The authors hypothesize that the Wenchuang earthquake may have induced a pulse of strongly disequilibrated fluids in the fault favoring accelerated crack sealing. Fault sealing is reported to have lasted a minimum of several years in the case of the Nojima fault zone
(Kitagawa et al., 2013) and potentially in the Tonghai earthquake fault (Ma et al., 2019). These observations show a high variability in the characteristic time of fault sealing that may result from very different contexts (Neuzil, 2019), different engineering backgrounds from the cited studies and the relatively low number of experimental studies related to the topic of fault self-sealing. Equation 6 describes chemical processes spanning over hundreds of years (Gratier, 2011). It follows that at shorter time scales (below a 100 years) other processes related to the evolution of the rheological and fluid transport properties of fault zones may dominate, which may lead to incomplete sealing of the fault. For example, following the concept of Barbour (2015), a background creeping rate that is higher than the rate of chemical processes may maintain a high background fault zone permeability.

Finally, we defined sealing as a return to close to undisturbed conditions. This is probably rather conservative as effective sealing may occur at some other threshold, for example, transition to diffusion-dominated transport or some other measurement of significance. Overall, what effective sealing might mean will be application dependent and the return to undisturbed values may look like an appealing criterion.

## 6. Conclusion

We have identified several key mechanisms contributing to the observed self-sealing phenomena following the activation of a shale fault.

1. Increase in effective normal and shear stress associated with the mechanical closure of the fault under depressurization conditions.

2. Steady-state compacting associated with slow shearing: this occurs within the range of laboratory values, considering the same state of stresses and similar argillaceous rock types.

3. Very long-term fault expansion: this may be linked to the swelling of clay minerals.

Our analysis suggests that these mechanisms play dominant roles in the self-sealing process over distinct time scales. Initially, a fast depressurization effect operates over a few days, followed by steady-state visco-plastic deformation over months, and eventually, swelling. The localization of these mechanisms may vary within the fault zone architecture, with the first primarily concentrated along the principal activated fault shear zone(s), while the second and third progressively extend throughout the entire fault zone volume.

We propose different fault transmissivity versus time relationships to characterize the data and predict sealing delay times for clay-rich fault zones. Due to the multiple competing processes involved, describing the fault sealing process with a single relationship proves challenging.

Our predictions indicate that, even under the most favorable conditions, sealing may take at least 50 years. However, it's important to note that our estimations are based on experiments conducted at shallow stress levels, involving a limited volume of fluid leakage and a brief fault activation duration.

While our data align reasonably well with laboratory-scale studies under similar stress and rock conditions, the variations in clay content within faults spanning multiple mudrock layers and the nature of fluids may influence fault sealing timescales differently than observed in our experiment. This underscores the necessity for additional observations at relevant basin-scale depths to enhance our understanding of these processes.

## Data Availability Statement

Data, including the CASSM source and receiver geometry, first arrival picks, P-wave arrival delay times, injection flow rate/pressure, the time-lapse travel-time tomography matrices, the DSS and the pulse pressure-v-time raw data can be found in the following OSF repository: https://osf.io/2rkvz/ (WRRGuglielmi2024).

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## Acknowledgments

This work was supported by the US Department of Energy (DOE), the Office of Nuclear Energy, Spent Fuel and Waste Science and Technology Campaign, under Contract Number DE-AC02-05CH11231 and the National Energy Technology Laboratory under the award number FP00013650. Secondary analysis support was provided by the U.S. Department of Energy, Office of Fossil Energy and Carbon Management (DOE FECM) under contract DE-FE00032058. Bill Lanyon's work was supported by Nationale Genossenschaft für die Lagerung radioaktiver Abfälle (NAGRA). The authors are grateful to the partners of the Mont Terri Project that contributed to the funding of the FS-B experiment: the Swiss Federal Office of Topography (Swisstopo), the Swiss Federal Nuclear Safety Inspectorate (ENSI), the Japanese 689 Atomic Energy Agency (JAEA), the Institute of Radioprotection and of Nuclear Safety 690 (IRSN, France), TOTAL SE, CHEVRON, SHELL, the Federal Institute for Geosciences and Natural Resources (BGR, Hannover), and the U.S. Department of Energy. The Mont Terri Project is an international research project for the hydrogeological, geochemical, and geotechnical characterizations of a clay formation (Opalinus Clay). We are grateful to the editor (G. Destouni), the associate editor and the two anonymous reviewers for their helpful comments.
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