Fractured Reservoir Characterization using Azimuthal AVO

Ordinary least squares is used to investigate the ability to detect changes in physical properties using Amplitude Versus Offset (AVO) information collected from seismic data. In order to characterize vertically aligned fractures within a reservoir, this method is extended to Azimuthal AVO (AVOA) analysis. Azimuthal AVO has the potential not only to detect fractured zones, but to spatially describe the fracture strike orientation and changes in fracture or fluid properties. Depending on the data acquisition geometry, signal-to-noise ratio, and extent of fracturing, AVOA analysis can be marginally successful. A study of the robustness and limitations of AVOA analysis is therefore first classified with synthetic data. These methods are then applied to seismic data collected during an Ocean Bottom Cable (OBC) survey over a known fractured reservoir.Massachusetts Institute of Technology. Earth Resources LaboratoryUnited States. Dept. of Energy (Grant DE-FC26-02NT15346)Eni S.p.A. (Firm

Characterization of Scattered Waves from Fractures by Estimating the Transfer Function Between Reflected Events Above and Below Each Interval

It is important to be able to detect and characterize naturally occurring fractures in reservoirs using surface seismic reflection data. 3D finite difference elastic modeling is used to create simulated surface seismic data over a three layer model and a five layer model. The elastic properties in the reservoir layer of each model are varied to simulate different amounts of vertical parallel fracturing. The presence of the fractures induces ringing wave trains primarily at times later than the bottom reservoir reflection. These ringy or scattered wave trains appear coherent on the seismograms recorded parallel to the fracture direction. While there are many scattered events on the seismograms recorded perpendicular to the direction of the fractures, these events appear to generally stack out during conventional processing. A method of characterizing and detecting scattering in intervals is developed by deconvolution to give an interval transfer function. The method is simple for the case of two isolated reflections, one from the top of the reservoir and the other from the bottom of the reservoir. The transfer function is computed using the top reflection as the input and the bottom reflection as the output. The transfer function then characterizes the effect of the scattering layer. A simple pulse shape indicates no scattering. A long ringy transfer function captures the scattering within the reservoir interval. When analyzing field data, it is rarely possible to isolate reflections. Therefore, an adaptation of the method is developed using autocorrelations of the wave trains above (as input) and below (as output) the interval of interest for the deconvolution process. The presence of fractures should be detectable from observed ringy transfer functions computed for each time interval. The fracture direction should be identifiable from azimuthal variations – there should be more ringiness in the direction parallel to fracturing. The method applied to ocean bottom cable field data at 4 locations show strong temporal and azimuthal variations of the transfer function which may be correlated to the known geology.Massachusetts Institute of Technology. Earth Resources LaboratoryUnited States. Dept. of Energy (Grant DE-FC26-02NT15346)Eni S.p.A. (Firm

Fracture Detection using Amplitude versus Offset and Azimuth Analysis of a 3D P-wave Seismic Dataset and Synthetic Examples

Amplitude versus offset (AVO) analysis of seismic reflection data has been a successful tool in describing changes in rock properties along a reflector. This method is extended to azimuthal AVO (AVOA) in order to characterize vertically aligned fractures within a reservoir, which can be important fluid migration pathways. AVOA analysis is performed on synthetic data using a least squares inversion method to investigate the effects of varying acquisition geometry, amount of noise, and fracture properties. These tests show that it is possible to detect the fractured layer and determine the fracture strike orientation under typical acquisition conditions. This method is also applied to field data collected during an Ocean Bottom Cable (OBC) survey. These data include a broad offset-azimuth range, which is important for the AVOA analysis. The fracture location and strike orientation recovered from the field data analysis are well correlated with borehole information from this area. Based on an understanding of AVOA behavior under synthetic conditions, this technique provides an effective methodology for describing the spatial variability of a fractured reservoir using 3D seismic data.Eni S.p.A. (Firm)United States. Dept. of Energy (Grant number DE-FC26-02NT15346)Massachusetts Institute of Technology. Earth Resources Laborator

Spatial Orientation And Distribution Of Reservoir Fractures From Scattered Seismic Energy

Shortened title: Fracture characterization from coda wavesWe present the details of a new method for determining the reflection and scattering characteristics of seismic energy from subsurface fractured formations. The method is based upon observations we have made from 3D finite difference modeling of the reflected and scattered seismic energy over discrete systems of vertical fractures. Regularly spaced, discrete vertical fractures impart a ringing coda type signature to any seismic energy which is transmitted through or reflected off of them. This signature varies in amplitude and coherence as a function of several parameters including: 1) the difference in angle between the orientation of the fractures and the acquisition direction, 2) the fracture spacing, 3) the wavelength of the illuminating seismic energy, and 4) the compliance, or stiffness, of the fractures. This coda energy is the most coherent when the acquisition direction is parallel to the strike of the fractures. It has the largest amplitude when the seismic wavelengths are tuned to the fracture spacing, and when the fractures have low stiffness. Our method uses surface seismic reflection traces to derive a transfer function which quantifies the change in an apparent source wavelet before and after propagating through a fractured interval. The transfer function for an interval with no or low amounts of scattering will be more spike-like and temporally compact. The transfer function for an interval with high scattering will ring and be less temporally compact. When a 3D survey is acquired with a full range of azimuths, the variation in the derived transfer functions allows us to identify subsurface areas with high fracturing and determine the strike of those fractures. We calibrated the method with model data and then applied it to the Emilio field with a fractured reservoir giving results which agree with known field measurements and previously published fracture orientations derived from PS anisotropy.Eni S.p.A. (Firm)United States. Dept. of Energy (Grant number DE-FC26-02NT15346)Massachusetts Institute of Technology. Earth Resources Laborator

Decadal-scale hotspot methane ebullition within lakes following abrupt permafrost thaw

Thermokarst lakes accelerate deep permafrost thaw and the mobilization of previously frozen soil organic carbon. This leads to microbial decomposition and large releases of carbon dioxide (CO2) and methane (CH4) that enhance climate warming. However, the time scale of permafrost-carbon emissions following thaw is not well known but is important for understanding how abrupt permafrost thaw impacts climate feedback. We combined field measurements and radiocarbon dating of CH4 ebullition with (a) an assessment of lake area changes delineated from high-resolution (1–2.5 m) optical imagery and (b) geophysical measurements of thaw bulbs (taliks) to determine the spatiotemporal dynamics of hotspot-seep CH4 ebullition in interior Alaska thermokarst lakes. Hotspot seeps are characterized as point-sources of high ebullition that release 14C-depleted CH4 from deep (up to tens of meters) within lake thaw bulbs year-round. Thermokarst lakes, initiated by a variety of factors, doubled in number and increased 37.5% in area from 1949 to 2009 as climate warmed. Approximately 80% of contemporary CH4 hotspot seeps were associated with this recent thermokarst activity, occurring where 60 years of abrupt thaw took place as a result of new and expanded lake areas. Hotspot occurrence diminished with distance from thermokarst lake margins. We attribute older 14C ages of CH4 released from hotspot seeps in older, expanding thermokarst lakes (14CCH4 20 079 ± 1227 years BP, mean ± standard error (s.e.m.) years) to deeper taliks (thaw bulbs) compared to younger 14CCH4 in new lakes (14CCH4 8526 ± 741 years BP) with shallower taliks. We find that smaller, non-hotspot ebullition seeps have younger 14C ages (expanding lakes 7473 ± 1762 years; new lakes 4742 ± 803 years) and that their emissions span a larger historic range. These observations provide a first-order constraint on the magnitude and decadal-scale duration of CH4-hotspot seep emissions following formation of thermokarst lakes as climate warms

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)