Seismic Diffraction Analysis of a Fluid Escape Pipe beneath the Submarine Gas Bubble Plume in the Haima Cold Seep Area

Pipe structures are considered as fluid conduits beneath cold seeps. These structures have been observed in many geological settings and are widely accepted as the most critical pathway for fluid migration. One of such pipe structures in the Haima cold seep region is investigated herein. The pipe structure extends from below the BSR and reaches the seafloor. It is characterized by a string of events with short and strong seismic amplitudes, similar to the string of bead reflections (SBRs) associated with small-scale caves in carbonate reservoirs. This leads to the hypothesis that multiple small-scale bodies exist within the pipe structure. We test this hypothesis by analysis of diffraction waves and numerical seismic modeling. Travel time pattern analysis indicates that the diffractors within the pipe structure caused the rich diffraction waves on the shot records, and the reversed polarity indicates that the diffractors have a lower impedance than the surrounding sediments. These low-impedance bodies are interpreted as gas pockets within the pipe structures. Based on these interpretations, a conceptual model is proposed to describe the fluid migration process within the pipe. Briefly, we propose that gas pockets within the pipe structure could be analogue to the magma chambers located beneath volcanoes and this may provide a new insight into how gases migrate through the pipe structure and reach the seafloor.

Using relative geologic time to constrain CNN-based seismic interpretation and property estimation

Three-dimensional seismic interpretation and property estimation is essential to subsurface mapping and characterization, in which machine learning, particularly supervised convolutional neural network (CNN) has been extensively implemented for improved efficiency and accuracy in the past years. In most seismic applications, however, the amount of available expert annotations is often limited, which raises the risk of overfitting a CNN particularly when only seismic amplitudes are used for learning. In such a case, the trained CNN would have poor generalization capability, causing the interpretation and property results of obvious artifacts, limited lateral consistency and thus restricted application to following interpretation/modeling procedures. This study proposes addressing such an issue by using relative geologic time (RGT), which explicitly preserves the large-scale continuity of seismic patterns, to constrain a seismic interpretation and/or property estimation CNN. Such constrained learning is enforced in twofold: (1) from the perspective of input, the RGT is used as an additional feature channel besides seismic amplitude; and more innovatively (2) the CNN has two output branches, with one for matching the target interpretation or properties and the other for reconstructing the RGT. In addition is the use of multiplicative regularization to facilitate the simultaneous minimization of the target-matching loss and the RGT-reconstruction loss. The performance of such an RGT-constrained CNN is validated by two examples, including facies identification in the Parihaka dataset and property estimation in the F3 Netherlands dataset. Compared to those purely from seismic amplitudes, both the facies and property predictions with using the proposed RGT constraint demonstrate significantly reduced artifacts and improved lateral consistency throughout a seismic survey.

Amangi field reservoir porosity and saturation estimation using seismic and well data

The scientific knowledge of mapping reservoir geometries provide useful displays for understanding the sediment fairway orientation and transport direction, they are not detailed enough to define the best quality well connected reservoir areas needed for planningdevelopment wells. Knowing that that long term development of this field will require excellent subsurface imaging to optimize the placement of future development and production wells, so to plan for this, we used strong reflected primaries (PP) and primary-shear (PS) waves imaging for the reservoir characterization. Porosity of two hydrocarbon reservoirs is investigated for the purpose of planning production operations in Amangi field of the Nigerian Delta. Well log derived porosities were measured at five appraisal wells in the field. Point information about the porosity of the reservoirs were determined from these well log data. However, lateral variations of porosity could not be delineated from measurements made only at the sparsely located wells in the field. A 3D seismic data covering an area of about 20 km x 17.5 km were acquired to delineate the extent of the porous sand. After careful data processing, the lateral variations of seismic amplitudes were transformed to changes in rock impedances, which, in turn, are indirectly related to porosity. In contrast with the sparse well observations, the 3D seismic method provided a dense and regular areal sampling of the acoustic properties of the reservoir intervals. The results of the transformation of the 3D anisotropic seismic reflection data were integrated with petrophysical measurements at the wells to significantly improve the spatial description of porosity in this field.

Locating flowing conduits in Karst using passive seismic deployments

<p>Karst is an important landscape in many locations incorporating many subterranean waterflow passages in the form of caves, conduits, and fractures. Although challenging, some karst structures can be imaged by active geophysical techniques however they generally cannot facilitate differentiation between flowing and non-flowing waterways. In this study, we aim to locate flowing conduits by passively capturing flow-induced seismic signals.</p><p>To gain a broad understanding of seismic source versus path effect in these complex structures and to help us design bespoke field experiments, we commence our study by undertaking 3D numerical simulation (using SPECFEM3D) for different cases of shallow and deep conduits. These choices are informed by known conduit geometries in Ireland (they have been dived). Spectral resonance, synthetic heat maps, and amplitude-based locations of synthetic data reveal interesting information regarding the conduit response.</p><p>Based on the results of these simulations, we designed the layout of a passive field experiment on karst on Pollnagran cave in County Roscommon, Ireland using 1Hz seismometers and 5 Hz Geophones. The karst deployment is also complemented by smaller experiments on surface rivers in order to help better understand observed signals. We also undertake an active hammer seismic survey at the site in order the build a model for future site-specific numerical simulations.</p><p>Consistent with numerical experiments, clear discrete frequencies associated with water flow are observed in the field data. A complex picture is emerging where the largest dived caves are not necessarily the flow structures with the largest seismic amplitudes.</p>

Estimation of relative source locations from seismic amplitude: application to earthquakes and tremors at Meakandake volcano, eastern Hokkaido, Japan

Although seismic amplitudes can be used to estimate event locations for volcanic tremors and other seismic events with unclear phase arrival times, the precision of such estimates is strongly affected by site amplification factors. Therefore, reduction of the influence of site amplification will allow more precise estimation of event locations by this method. Here, we propose a new method to estimate relative event locations using seismic amplitudes. We use the amplitude ratio between two seismic events at a given station to cancel out the effect of the site amplification factor at that station. By assuming that the difference between the hypocentral distances of these events is much smaller than their hypocentral distances themselves, we derive a system of linear equations for the differences in relative event locations. This formulation is similar to that of a master event location method that uses differences in phase arrival times. We applied our new method to earthquakes and tremors at Meakandake volcano, eastern Hokkaido, Japan. Comparison of the hypocentral distributions of volcano-tectonic earthquakes obtained thereby with those obtained from phase arrival times confirmed the validity of our new method. Moreover, our method clearly identified source migration among three source regions in the tremor on 16 November 2008, consistent with previous interpretations of other geophysical observations in our study area. Our method will thus be useful for detailed analyses of seismic events whose onset times are ambiguous.

The Silencing of U.S. Campuses Following the COVID-19 Response: Evaluating Root Mean Square Seismic Amplitudes Using Power Spectral Density Data

In response to the COVID-19 global pandemic, many populated and active regions have become deserted and show significant reductions in their background seismicity, especially campuses across the United States (U.S.). Seismic sensors located in the vicinity of or within U.S. campuses show that anthropogenic seismic noise remains elevated during the ordinary, nonpandemic, academic year, only subduing during periods of recess (e.g., winter break). Here, we use power spectral density (PSD) data computed by the Incorporated Research Institutions for Seismology Data Management Center for quality assessment to calculate root mean square (rms) amplitude and analyze the effects of the COVID-19 school closures. We processed and analyzed PSD data for 46 seismic stations located within 50 m of a U.S. university or college. Results show that 42 campus stations show an overall rms drop following a statewide school closure.

Robust Empirical Time–Frequency Relations for Seismic Spectral Amplitudes, Part 2: Model Uncertainty and Optimal Parameterization

ABSTRACT In a companion article, Safarshahi and Morozov (2020) argued that construction of distance- and frequency-dependent models for seismic-wave amplitudes should include four general elements: (1) a sufficiently detailed (parametric or nonparametric) model of frequency-independent spreading, capturing all essential features of observations; (2) model parameters with well-defined and nonoverlapping physical meanings; (3) joint inversion for multiple parameters, including the geometrical spreading, Q, κ, and source and receiver couplings; and (4) the use of additional dataset-specific criteria of model quality, while fitting the logarithms of seismic amplitudes. Some of these elements are present in existing models, but, taken together, they are poorly understood and require an integrated approach. Such an approach was illustrated by detailed analysis of an S-wave amplitude dataset from southern Iran. The resulting model is based on a frequency-independent Q, and matches the data closer than conventional models and across the entire epicentral-distance range. Here, we complete the analysis of this model by evaluating the uncertainties and trade-offs of its parameters. Two types of trade-offs are differentiated: one caused by a (possibly) limited model parameterization and the second due to statistical data errors. Data bootstrapping shows that with adequate parameterization, attenuation properties Q, κ, and geometrical spreading parameters are resolved well and show moderate trade-offs due to measurement errors. Using the principal component analysis of these trade-offs, an optimal (trade-off free) parameterization of seismic amplitudes is obtained. By contrast, when assuming theoretical values for certain model parameters and using multistep inversion procedures (as commonly done), parameter trade-offs increase dramatically and become difficult to assess. In particular, the frequency-dependent Q correlates with the distribution of the source and receiver-site factors, and also with biases in the resulting median data residuals. In the new model, these trade-offs are removed using an improved parameterization of geometrical spreading, constant Q, and model quality constraints.

Are bright spots always hydrocarbons? A case study in the Taranaki Basin, New Zealand

In the shallower regions of the 3D Nimitz seismic survey, there exist multiple interesting bright seismic amplitude anomalies. These anomalies, or funny looking things, occur in a confined spatial and temporal region of the seismic. They have a concave-up seismic appearance along the cross section. Bright seismic amplitudes can be a direct hydrocarbon indicator, or they can be representative of strong lithologic contrasts and/or acquisition artifacts. We have set out to investigate misinterpreted seismic anomalies along cross-sectional lines. Therefore, we apply seismic attributes to indicate that these bright spot features, which we interpret to be submarine gullies looking along time-slice intersections, can possibly be mistaken for hydrocarbon anomalies in a cross-sectional view. However, we cannot fully rule out the presence of hydrocarbons because it is common for gas sands to create similar anomalies. Previously drilled wells within the survey (Korimako-1 and Tarapunga-1) point to a lack of hydrocarbon potential in the subsurface. Although it is possible that these bright spots are due to hydrocarbon presence, we develop a more likely hypothesis: The lithology of the interfluve sediments is similar to the gully-margin drapes but differs from the gully sediment fill. Funny looking thing (FLT): Submarine gullies Seismic appearance: High-amplitude spotted features Alternative interpretations: Lithologic anomalies, gas seeps, bright spots Features with a similar appearance: Gas accumulation, sediment fills in limestone paleocaves Formation: Giant Foresets Formation Age: Pleistocene Location: Taranaki Basin, New Zealand Seismic data: Nimitz 3D (cropped volume) Analysis tools: Curvature, instantaneous frequency, and sweetness attributes; well reports