Seismic ground-roll noise attenuation using deep learning

We propose to adopt a deep learning based framework using generative adversarial networks for ground-roll attenuation in land seismic data. Accounting for the non-stationary properties of seismic data and the associated ground-roll noise, we create training labels using local time–frequency transform and regularized non-stationary regression. The basic idea is to train the network using a few shot gathers such that the network can learn the weights associated with noise attenuation for the training shot gathers. We then apply the learned weights to test ground-roll attenuation on shot gathers, that are not a part of training input to obtain the desired signal. This approach gives results similar to local time–frequency transform and regularized non-stationary regression but at a significantly reduced computational cost. The proposed approach automates the ground-roll attenuation process without requiring any manual input in picking the parameters for each shot gather other than in the training data. Tests on field-data examples verify the effectiveness of the proposed approach.     

Approximate traveltime inversion in downhole microseismic monitoring

In downhole microseismic monitoring, accurate event location relies on the accuracy of the velocity model. The model can be estimated along with event locations. Anisotropic models are important to get accurate event locations. Taking anisotropy into account makes it possible to use additional data – two S-wave arrivals generated due to shear-wave splitting. However, anisotropic ray tracing requires iterative procedures for computing group velocities, which may become unstable around caustics. As a result, anisotropic kinematic inversion may become time consuming. In this paper, we explore the idea of using simplified ray tracing to locate events and estimate medium parameters. In the simplified ray-tracing algorithm, the group velocity is assumed to be equal to phase velocity in both magnitude and direction. This assumption makes the ray-tracing algorithm five times faster compared to ray tracing based on exact equations. We present a set of tests showing that given perforation-shot data, one can use inversion based on simplified ray-tracing even for moderate-to-strong anisotropic models. When there are no perforation shots, event-location errors may become too large for moderately anisotropic media.     

The international conference “Vortices and coherent structures: from ocean to microfluids”, Vladivostok,Russia, 28–31 August 2017

The international conference “Vortices and coherent structures: from ocean to microfluids” was held at the Pacific Oceanological Institute of the Russian Academy of Sciences in Vladivostok (Russia) from August 28 to August 31, 2017. The event gathered experimentalists and theoreticians, oceanographers and physicists, with a common interest in observing and modelling fluid flows in different media, from the ocean to laboratory flows. It was a fruitful idea to bring together researchers from a variety of backgrounds to benefit from a vigorous discussion of concepts across different disciplines in oceanography and hydrodynamics.

     

Evolution of permafrost in China during the last 20 ka

The formation and evolution of permafrost in China during the last 20 ka were reconstructed on the basis of large amount of paleo-permafrost remains and paleo-periglacial evidence, as well as paleo-glacial landforms, paleo-flora and paleofauna records. The results indicate that, during the local Last Glacial Maximum(LLGM) or local Last Permafrost Maximum(LLPMax), the extent of permafrost of China reached 5.3×106-5.4×106 km2, or thrice that of today, but permafrost shrank to only0.80×106-0.85×106 km2, or 50% that of present, during the local Holocene Megathermal Period(LHMP), or the local Last Permafrost Minimum(LLPMin). On the basis of the dating of periglacial remains and their distributive features, the extent of permafrost in China was delineated for the two periods of LLGM(LLPMax) and LHMP(LLPMin), and the evolution of permafrost in China was divided into seven periods as follows:(1) LLGM in Late Pleistocene(ca. 20000 to 13000-10800 a BP)with extensive evidence for the presence of intensive ice-wedge expansion for outlining its LLPMax extent;(2) A period of dramatically changing climate during the early Holocene(10800 to 8500-7000 a BP) when permafrost remained relatively stable but with a general trend of shrinking areal extent;(3) The LHMP in the Mid-Holocene(8500-7000 to 4000-3000 a BP)when permafrost degraded intensively and extensively, and shrank to the LLPMin;(4) Neoglaciation during the late Holocene(4000-3000 to 1000 a BP, when permafrost again expanded;(5) Medieval Warming Period(MWP) in the late Holocene(1000-500 a BP) when permafrost was in a relative decline;(6) Little Ice Age(LIA) in the late Holocene(500-100 a BP), when permafrost relatively expanded, and;(7) Recent warming(during the 20 th century), when permafrost continuously degraded and still is degrading. The paleo-climate, geography and paleopermafrost extents and other features were reconstructed for each of these seven periods.     

Time‐lapse pre‐stack seismic data registration and inversion for CO2 sequestration study at Cranfield

Pre‐stack seismic data are indicative of subsurface elastic properties within the amplitude versus offset characteristic and can be used to detect elastic rock property changes caused by injection. We perform time‐lapse pre‐stack 3‐D seismic data analysis for monitoring sequestration at Cranfield. The time‐lapse amplitude differences of Cranfield datasets are found entangled with time‐shifts. To disentangle these two characters, we apply a local‐correlation‐based warping method to register the time‐lapse pre‐stack datasets, which can effectively separate the time‐shift from the time‐lapse seismic amplitude difference without changing the original amplitudes. We demonstrate the effectiveness of our registration method by evaluating the inverted elastic properties. These inverted time‐lapse elastic properties can be reliably used for monitoring plumes.     

Lagrangian study of temporal changes of a surface flow through the Kamchatka Strait

Using Lagrangian methods, we analyze a 20-year-long estimate of water flux through the Kamchatka Strait in the northern North Pacific based on AVISO velocity field. It sheds new light on the flux pattern and its variability on annual and monthly time scales. Strong seasonality in surface outflow through the strait could be explained by temporal changes in the wind stress over the northern and western Bering Sea slopes. Interannual changes in a surface outflow through the Kamchatka Strait correlate significantly with the Near Strait inflow and Bering Strait outflow. Enhanced westward surface flow of the Alaskan Stream across the 174°E section in the northern North Pacific is accompanied by an increased inflow into the Bering Sea through the Near Strait. In summer, the surface flow pattern in the Kamchatka Strait is determined by the passage of anticyclonic and cyclonic mesoscale eddies. The wind stress over the Bering basin in winter–spring is responsible for eddy generation in the region.     

Open and coastal seas interactions south of Japan represented by an ensemble Kalman filter

We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have adopted the local ensemble transformation Kalman filter algorithm based on 20 members’ ensemble simulations of the parallelized Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability.     

Estimation of methane fluxes from bottom sediments of Lake Baikal

Methane bubble fluxes in gas flares from bottom sediments in Lake Baikal were estimated for the first time using hydroacoustic methods. Earlier work has demonstrated the occurrence of gas seeps both inside and outside of areas where bottom simulating reflectors were identified in seismic profiles. Fluxes ranged from 14 to 216 tons per year, with the flux for the entire area of the central and southern basins ranging from 1,400 to 2,800 tons per year. Comparison with other water bodies showed that fluxes from the most intensive Baikal flares were similar to those in the Norwegian and Okhotsk seas. Gas hydrates decompose at the lower boundary of the gas hydrate stability zone due to sedimentation. Calculation of the amount of methane produced due to sedimentation gave a total of between 2,600 and 14,000 tons per year for the central and southern basins of the lake. Based on rough estimation, the total flux from shallow- and deep-water gas seeps is similar to the amount of methane produced due to sedimentation. This suggests that gas hydrates possibly occupy much more than 10?% of the pore volume near the base of the gas hydrate stability zone, or that there are other reasons for gas hydrate dissociation and bubble flux from these bottom sediments.