SUMMARY: The harmonic electromagnetic noise produced by anthropic electrical structures is a critical component of the global noise affecting geophysical signals and increasing data uncertainty. It is composed of a series of harmonic signals whose frequencies are multiple integers of the fundamental frequency specific to the electrical noise source. To date, most model-based noise removal strategies assume that the fundamental frequency constraining the harmonic noise is single and constant over the duration of the geophysical record. In this paper, we demonstrate that classical harmonic processing methods lose efficacy when these assumptions are not valid. We present several surface nuclear magnetic resonance field data sets, which testify the increasing probability of recording the harmonic noise with such multiple or unstable frequency content. For each case (multiple frequencies or unstable frequency) we propose new processing strategies, namely, the 2-D grid-search and the segmentation approach, respectively, which efficiently manage to remove the harmonic noise in these difficult conditions. In the process, we also apply a fast frequency estimator called the Nyman, Gaiser and Saucier estimation method, which shows equivalent performance as classical estimators while allowing a reduction of the computing time by a factor of 2.5.

Passive (ambient noise) seismic interferometry provides multiple ways to gather information about the subsurface seismic properties using recordings of the seismic ambient noise signal. While the first developments and applications of this method showed a useful capacity to either image geological contrasts or monitor the structural properties of the soil, an increasing momentum is observed toward applications related to fluid monitoring of different types (liquid, gas), at all the scales of the subsurface (from meters to kilometers). In this paper we summarize the existing possibilities and technics of seismic interferometry analysis for subsurface fluid detection and characterization and elaborate on their respective deployment in different contexts. We also present a new approach based on estimating and continuously measuring seismic attenuation proxy within interferometric-based surface wavefields, which show a high sensitivity to fluid dynamics and the associated petrophysical variations. The method is illustrated through a field case study related to geological gas storage monitoring, and we elaborate on its potential respective deployment at the industrial scale and for different applications. En sismique passive, l'interférométrie du bruit sismique ambiant permet de recueillir des informations sur les propriétés sismiques du soussol à l'aide d’enregistrements du signal sismique continu. Alors que les premiers développements et applications de cette méthode ont montré une capacité à imager les contrastes géologiques ou à surveiller les propriétés structurelles du sol, un élan croissant est observé vers des applications liées à la surveillance des fluides de différents types (liquide, gaz), à toutes les échelles de la subsurface (de quelques mètres à quelques kilomètres). Dans cet article, nous résumons les possibilités et les techniques existantes d'analyse par interférométrie sismique pour la détection et la caractérisation des fluides de subsurface et nous discutons leur déploiement respectif dans différents contextes appliqués. Nous présentons également une nouvelle approche basée sur l'estimation continue des variations d'atténuation sismique, via l’analyse de d'ondes de surface reconstruites par interférométrie. Cette méthode montre une grande sensibilité à la dynamique des fluides et aux variations pétrophysiques associées. Un cas d’étude est présenté dans le contexte de la surveillance de stockage géologique de gaz, et nous discutons son déploiement potentiel à l'échelle industrielle, pour différentes applications.

The surface Nuclear Magnetic Resonance method is gaining momentum as an efficient geophysical method for the detection and characterization of groundwater. However, the method still suffers from a low signal to noise ratio mostly due to electromagnetic noise of anthropic origin.To solve this problem, signal processing in surface nuclear magnetic resonance surveys often relies on the reference-based noise cancellation technique. This method consists of capturing the main characteristics of the noise through a secondary loop ideally located and obtaining an estimate of the noise affecting the primary loop which can be subtracted from the noisy sNMR signal.The main problem associated with the method occurs when the spatial distribution of the noise is heterogeneous, which can result in a low correlation between the reference loop and the primary loop, and hence in a poor noise reduction. Difficulties may also arise when the field survey location prevents the display of a reference loop for logistics or physical reasons.To remediate these situations we have investigated the possibility of recording noise-only signals through the primary loop, prior to the sNMR measurement, and use those signals as references for subsequent calculation of the local transfer function. The correlation between a series of noise-only signal recorded on a primary loop was analyzed through the computation of the magnitude squared coherence function, and comparison was made with noise records from a secondary loop. The analysis demonstrates that temporal reference noise cancellation (TRNC) can provide more efficient noise reduction results than the classical spatial reference noise cancellation if the temporal noise-only database is large enough.Such a technique would be particularly suited for the development of long-term sNMR monitoring systems, where noise records could be acquired for long periods without any difficulty. In addition to two field survey examples, we present a synthetic statistical analysis to estimate the minimal volume of the signal database required for optimal noise reduction.