Géli, Louis

In their comment, Yamomoto and co-authors are primarily concerned with the existence and effect of large values of minimum and maximum phase residuals in our analysis and locations using the 2014 observations, as listed in Tables S7 and S8 in the supplementary material of our paper (Batsi et al, 2018). We retain these large residuals in the tables and analysis since they have vanishingly small effect on the NonLinLoc locations, since the used, equal differential time (EDT) location algorithm (Lomax, 2008; Lomax et al., 2009) is highly robust to outlier readings. In the case of our Marmara study, phases with residuals larger than 1-2sec have near zero weight in the locations and corrected phase data. However, we agree the larger residuals may have had adverse effect on the generation of station corrections, though this, in turn, would also be mitigated by the robust location procedure. As a result, we consider that the location discrepancies between Yamomoto et al (2017) and Batsi et al. (2018) are not due to effects of excessively large residuals on the station corrections or locations. Instead, we propose that, as in many seismicity studies, error and uncertainty in the absolute hypocenter locations is primarily related to error in the velocity model and insufficient geometrical coverage of the source zones by the available seismic stations. To support this proposition, and following the recommendation of Yamamoto et al., we recalculate station corrections for our 2014 data set and then relocate the 14 common events (Table A) that were located by both Yamamoto et al. (2017) and ourselves (see Table 9 in Batsi et al., 2018, with correct Yamomoto’s location for event 3: 40.8058N, 27.9504E, 13.411km). We first generate station corrections as described in Batsi et al. (2018) using all events from 2014 which comply with the Batsi et al. (2018) location criteria (number of stations ≥ 5; number of phases ≥ 6; (3) root mean square (rms) location error ≤ 0.5s; azimuthal gap ≤ 180°), except that we explicitly exclude from the analysis any P or S residuals > 3.0s when generating station corrections (Table B). We then relocate in the high‐resolution, 3D, P‐velocity model, as described in Batsi et al. (2018), the 14 common events using these station corrections. Figure 1 shows, for the 14 common events listed I Table A, the absolute NonLinLoc maximum likelihood and expectation hypocenters, and location probability density (pdf) clouds for our absolute relocations, along with the corresponding Yamamoto et al. (2017) double-difference relocations and Batsi et (2018) relative (NonDiffLoc) locations. For sake of clarity, calculation results are detailed in Figure 2 for each individual event (1 to 14). The full information on the earthquake location spatial uncertainty is shown by the pdf clouds, while the maximum-likelihood hypocenter is the best solution point and the expectation hypocenter shows a weighted mean or “center of mass” of the cloud. The pdf clouds show a large uncertainty in hypocenter depth, the formal standard error in depth ranges from 2-9km. There is also a large separation between the maximum likelihood and expectation hypocenters for some events. These results underline the large uncertainty in depth determination and corresponding instability in any one-point measure chosen as a hypocenter. However, despite these uncertainties and instabilities, the Yamamoto et al. (2017) hypocenters remain generally deeper than the maximum likelihood and expectation hypocenters for our relocations, positioned towards the deeper uncertainty limits of our locations (e.g. the lower portion of the pdf clouds), and the Yamamoto et al. (2017) epicenters fall near the Main Marmara fault (MMF) while our relocated epicenters define off axis seismicity, along secondary faults from the MMF system. Thus our relocated events, which explicitly exclude excessively large residuals, still show differences with the Yamamoto et al. (2017) events, but not as large as those we found in our original study. Based on our recalculated NonLinLoc absolute locations, we suspect that  Yamamoto et al (2017) results are systematically too deep and Batsi et al (2018) systematically too shallow, compared to what should be expected. These differences in epicenter and depth, along with the size and shape of the pdf clouds for our relocations, are most easily explained by differences in the 3D velocity models and by differences in available stations and the consequent network geometry . However, while the epicentral distances at most of the OBS stations are shorter than the focal depths, as noted by Yamomoto et al., the elongation of our pdf clouds in depth suggests that an increase in network aperture with more distant stations, along with an accurate 3D model, is required to better constrain depth. High-resolution earthquake epicenter and depth determinations below the Sea of Marmara is a difficult problem, yet of critical importance. To better understand why the two studies produce different results, and to obtain the best possible locations, the best action is to increase the number of constraints by merging the two OBS datasets, and examine, step by step, the effects of locations methods, network geometry and 3D velocity models from the two studies. Sharing the data (or phase picks and model) would provide an unique opportunity to give real, direct insight into these issues. We suspect that epicenters will shift as a function of used velocity model and station set, and that in all cases depth uncertainty is large, as is clearly represented in the NonLinLoc location, pdf clouds, while linearized location error estimates usually show lower uncertainty.

MarsiteCruise was undertaken in October/November 2014 in the Sea of Marmara to gain detailed insight into the fate of fluids migrating within the sedimentary column and partially released into the water column. The overall objective of the project was to achieve a more global understanding of cold-seep dynamics in the context of a major active strike-slip fault. Five remotely operated vehicle (ROV) dives were performed at selected areas along the North Anatolian Fault and inherited faults. To efficiently detect, select and sample the gas seeps, we applied an original procedure. It combines sequentially (1) the acquisition of ship-borne multibeam acoustic data from the water column prior to each dive to detect gas emission sites and to design the tracks of the ROV dives, (2) in situ and real-time Raman spectroscopy analysis of the gas stream, and (3) onboard determination of molecular and isotopic compositions of the collected gas bubbles. The in situ Raman spectroscopy was used as a decision-making tool to evaluate the need for continuing with the sampling of gases from the discovered seep, or to move to another one. Push cores were gathered to study buried carbonates and pore waters at the surficial sediment, while CTD-Rosette allowed collecting samples to measure dissolved-methane concentration within the water column followed by a comparison with measurements from samples collected with the submersible Nautile during the Marnaut cruise in 2007. Overall, the visited sites were characterized by a wide diversity of seeps. CO2- and oil-rich seeps were found at the westernmost part of the sea in the Tekirdag Basin, while amphipods, anemones and coral populated the sites visited at the easternmost part in the Cinarcik Basin. Methane-derived authigenic carbonates and bacterial mats were widespread on the seafloor at all sites with variable size and distributions. The measured methane concentrations in the water column were up to 377 μmol, and the dissolved pore-water profiles indicated the occurrence of sulfate depleting processes accompanied with carbonate precipitation. The pore-water profiles display evidence of biogeochemical transformations leading to the fast depletion of seawater sulfate within the first 25-cm depth of the sediment. These results show that the North Anatolian Fault and inherited faults are important migration paths for fluids for which a significant part is discharged into the water column, contributing to the increase of methane concentration at the bottom seawater and favoring the development of specific ecosystems

A detailed study, based on ocean-bottom seismometers (OBSs) recordings from two recording periods (3.5 months in 2011 and 2 months in 2014) and on a high-resolution, 3D velocity model, is presented here, which provides an alternative view of the microseismicity along the submerged section of the North Anatolian fault (NAF) within the western Sea of Marmara (SoM). The nonlinear probabilistic software packages of NonLinLoc and NLDiffLoc were used for locating earthquakes. Only earthquakes that comply with the following location criteria (e.g., representing 20% of the total amount of events) were considered for analysis: (1) number of stations ≥ 5; (2) number of phases ≥ 6, including both P and S; (3) root mean square (rms) location error ≤ 0:5 s; and (4) azimuthal gap ≤ 180°. P and S travel times suggest that there are strong velocity anomalies along the Western High, with low Vp, low Vs, and ultra-high Vp=Vs in areas where mud volcanoes and gas-prone sediment layers are known to be present. The location results indicate that not all earthquakes occurred as strike-slip events at crustal depths (> 8 km) along the axis of the Main Marmara fault (MMF). In contrast, the following features were observed: (1) a significant number of earthquakes occurred off-axis (e.g., 24%), with predominantly normal focal mechanisms, at depths between 2 and 6 km, along tectonically active, structural trends oriented east–west or southwest–northeast, and (2) a great number of earthquakes was also found to occur within the upper sediment layers (at depths < 2 km), particularly in the areas where free gas is suspected to exist, based on high-resolution 3D seismics (e.g., 28%). Part of this ultra-shallow seismicity appears to occur in response to deep earthquakes of intermediate (ML ∼ 4–5) magnitude. Resolving the depth of the shallow seismicity requires adequate experimental design ensuring source–receiver distances of the same order as hypocentral depths. To reach this objective, deep-seafloor observatories with a sufficient number of geophone sensors near the fault trace are needed.