a b s t r a c tConventional 3D seismic data provides direct evidence for glacial influence during the early Pleistocene sedimentation in the Central North Sea. We identify iceberg ploughmarks as dim linear to curve-linear features in three early Pleistocene horizons that have high reflection amplitude compared to adjacent horizons. The anomalous horizons are interpreted to be reflections from thin sandy layers saturated with gas. The gas acts as a contrast liquid illuminating the thin sand layers. The reason for this is the difference in acoustic properties between water and gas saturated sand layers. The combination of thin bed effects and shallow gas makes the iceberg ploughmarks easily detectable as dim features in seismic reflection amplitude maps. Our interpretation is based on analysis of real seismic data, well logs and modeled seismic response. The methods we use include interpretation of horizons followed by extraction of reflection amplitudes, well log analysis, pre-stack amplitude versus offset analysis of high resolution 2D seismic data and time-lapse analysis of seismic. Seismic modeling is performed to study interactions between thin sand beds, shallow gas and iceberg ploughmarks. A new trapping mechanism for shallow gas is presented and seismic modeling of this trap strengthens our interpretation. The trap is created by iceberg ploughmarks in sandy layers that are covered by finer and less permeable sediments. For this area we find that conventional seismic interpretation is superior to the much used method of studying seismic time-slices for detection of iceberg ploughmarks, both with respect to time and detectability. This study shows that the interpreter should look for high amplitude horizons with amplitude variations laterally when trying to detect iceberg ploughmarks.

Recent advances in marine broadband seismic data acquisition have led to a range of new air-gun source configurations. The air-gun arrays have conventionally been kept at a constant depth, but to attenuate the source-side ghost reflection, new source strategies involving multiple source depths have been proposed. The bubble-time period for an air-gun bubble is dependent on, among many parameters, the firing depth. We use quasi near-field measurements of air-gun signatures to validate a version of the well-known source scaling law in which the characteristic bubble-time period is used as the scale. We find that the source scaling law can be used to estimate a source signature from one depth knowing the source signature at a different depth from the same gun. Furthermore, we derive a correction term to the Rayleigh-Willis bubble-time equation to correct for the fact that interaction between the bubble and free surface reduces the bubble-time period. This correction term improves our results significantly for air guns positioned close to the air-water interface. The error between the estimated and measured source signatures is dependent on the difference in source depth. For a depth difference of [Formula: see text], we estimate signatures that have NRMS differences ranging between 5% and 6% from the measured signature at the given depth and between 8% and 12% when the difference is [Formula: see text].

Summary Distributed acoustic sensing (DAS) is used to monitor production and injection wells in real time. Here we present theory, data examples, and interpretation of low-frequency (LF)-DAS data acquired on fiber-optic (FO) cables clamped to the production tubing. We show that these data give unprecedented insights into the well and serve as a tool for qualitative analysis of well integrity, well operations, and production. By understanding these data, we show that we, for example, can detect leaks, monitor valve performance, and detect the liquid level in Annulus A. While in-well DAS’s sensitivity to changes in temperature over time is well known, its sensitivity to pressure and flow at low frequencies has not been well understood. Here, we show that the LF-DAS response is multifaceted and dependent on the fluid content of the different tubulars in a well, the casing, and completion design, and if a valve is open or closed. Very often a pressure response is seen due to an accompanied temperature effect; while this complicates the overall picture for quantitative data analysis, qualitative interpretation can be made simple. Understanding these processes in LF-DAS data forms the foundation for developing automated interpretation algorithms in the future.

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In marine seismic data acquisition, varying the source depth along a sail line gives diversity in sequential shot gather frequency spectra. Undesired alterations of the frequency spectra are created by the source ghost and by air-gun bubble oscillations. By deliberately varying the source depth along a sail line, it is possible to obtain a seismic data set that will have energy more evenly distributed within the main frequency band of the source output. This is obtained when data acquired with different source depths are stacked in imaging. We formulated a simple inverse problem that seeks to find the optimal distribution of source depths over a sequential series of shots that shape the amplitude spectrum of the final image into a desired shape. We assumed that the data are receiver-side deghosted, that designature could be applied to each shot gather, and that the shot gathers could be redatumed to a common datum prior to imaging.