The authors acknowledge the financial support of NSFC to WT (grant no. 41272368) and QKX (grant no. 41630205).

NOTE: The data processing procedures include: synthetic seismogram calculation, synthetic-real seismic trace correlation, and geo-body extraction. Below are the step-by-step details of each procedure.
1. Calculation of Synthetic Seismogram
<ol>
	<li>Calculate the acoustic impedance at each interval of the down-well logging curve. 
	NOTE: Acoustic impedance is the product of &#39;seismic wave velocities&#39; and &#39;density&#39; (&#961;*&#957;)). The data are often averaged to sampling intervals larger than 1 ft, in order to reduce the computation time and aliasing.</li>
	<li>Calculate the reflection coefficients (R0) at each interface by using the acoustic impedance calculation: 
	<img alt="Equation" src="/files/ftp_upload/55930/55930eq1.jpg" /> 
	where &#957;1 and &#957;2 are the averaged velocities of the layers below and above the interface, respectively; &#961;1 and &#961;2 are the corresponding averaged densities.
	<ol>
		<li>If the well does not intersect the igneous bodies, use nearby wells that have intersected the target rocks to obtain the parameters (velocity, density, etc.).</li>
	</ol>
	</li>
	<li>Chose a wavelet that has an amplitude and phase spectrum similar to that of the nearby seismic data.</li>
	<li>Convolve the synthetic wavelet with the reflection series for the entire well survey and generate a synthetic seismic trace. The final simulated seismic trace T(t) can be described by the convolutional model as below: 
	<img alt="Equation" src="/files/ftp_upload/55930/55930eq2.jpg" /> 
	where R0(t) is the reflection coefficient, w(t) is the wavelet and n(t) is the noise.</li>
	<li>If the frequency of the seismic data has large variations throughout the whole well, re-compute the synthetic seismic trace using a wavelet with a different phase and a dominant frequency at different depth intervals.
	<ol>
		<li>Repeat the process if the match between the synthetic trace and the seismic data is not satisfactory.</li>
	</ol>
	</li>
	<li>Perform the calculation with the provided software (e.g., Petrel E&#38;P Software Platform).
	<ol>
		<li>Start the software. Select File | Open Project | and then select the demo research project tlm (users can select their own desired projects). The project should contain well data, wired log, well tops, seismic cube, and interpretation surface in the research area.</li>
		<li>Click on Home | Windows | 2D Windows | 3D Windows to open two display windows to show the data sets according to user&#39;s preference.</li>
		<li>In the &#34;Wells Tree of Input Pane&#34;, right click the desired well. Open the Settings window of the well and select the Time tab to create a new time log. Select Velocity Function, then select DT data in the new time log. Click the OK button to close settings window. A new one-way time log is automatically created and will be shown in the &#34;Wells Tree of Input Pane&#34;. 
		NOTE: A one-way time log is a time-depth relationship of this well. Wired log domains can be transformed to time domains and be shown in the time domain window.</li>
		<li>Activate an existing 3D Window by clicking the displayed window. If there is no 3D Window displayed, create a new 3D Window by clicking Home | Windows | 3D Windows. Select TWT in the toolbar of the 3D Window to show the 3D Window in time domain.</li>
		<li>Select representative wired logs (such as &#39;GR&#39;, &#39;DT&#39;, or &#39;RT&#39;) in the Wells Tree to show them in the 3D Window; at the same time, select the seismic profile in the &#39;seismic&#39; tree of the &#39;input&#39; pane to show them in the same 3D Window.</li>
		<li>Use the Manipulate Plane tool in the toolbar of the 3D Window to adjust the location of the profile to intersect the well; the user will see that the wired log has been transformed to the time domain and displayed with the seismic profile in the same 3D window.</li>
		<li>Click Seismic Interpretation | Seismic Well Tie | Seismic Well Tie Process. Choose Integrated Seismic Well Tie in the type of study row, and add desired well in the Well row. Choose calibrated one-way time log as time-depth relationship in the TDR row of the input tab, choose seismic cube in the seismic row. Choose any log in the RC calculation method.</li>
		<li>Click Launch Wavelet Toolbox to create a Ricker wavelet to apply in this process. Click OK and a new well section window and synthetic seismogram display will be created.</li>
	</ol>
	</li>
</ol>
2. Correlate the Synthetic Traces with the Real Seismic Reflectors
<ol>
	<li>Use an automated correlation application, like Seismic Well Tie in the platform, to adapt the resulting synthetic trace to the vertical scale of the seismic section.</li>
	<li>Adjust the synthetic seismogram to increase the overlapping of high amplitude reflectors of the synthetic trace and real trace.</li>
	<li>Adjust the synthetic seismogram and the real trace repeatedly. When the overlapping trace reaches the maximum, the interpreter has reached the &#34;best fits&#34; between the obtained synthetic seismogram and real traces.
	<ol>
		<li>Repeat the process until the correlations reach the desired level.</li>
	</ol>
	</li>
	<li>Perform the correlation with the provided software.
	<ol>
		<li>Activate the window created in step 1.6.3, which is the one-way time log automatically created from the acoustic log. 
		NOTE: This automatically created &#39;one-way time log&#39; is not perfectly correlated with the real seismic reflectors. The users should calibrate the correlations between the one-way time log and the real seismic reflectors.</li>
		<li>To calibrate their correlations, choose a continual and representative reflector that is intersected by the well. Then manually adjust the depth of the well log. For example, to adjust the depth of the DT log, right click the One-Way Time Log in well tree | select the Calculator tool | then add a small time increment (for example, 10 ms) by typing &#39;DT=DT+10&#39; in the input dialog of the Calculator tool.</li>
		<li>If the &#39;10 ms&#39; increment is too large or too small, change the increment to another time (can be negative value) in the &#39;calculator&#39; tool. Check the correlation between the well log and the selected seismic horizon repeatedly and then adjust the time increment repeatedly, until the correlation is perfectly calibrated.</li>
	</ol>
	</li>
</ol>
3. Extraction of Basaltic Sills
<ol>
	<li>Pick 2 high-amplitude reflectors encasing the target sills. 
	NOTE: Most intrusions are expressed in seismic data as tuned reflection packages, whereby the reflections from the upper and lower intrusion contacts cannot be distinguished. Tuning occurs when the vertical intrusion thickness is between &#955;/4 and &#955;/8 (&#955; is seismic wavelength)19. Therefore, sills are shown as a set of strong reflections in the seismic section, and their apparent thickness is false.</li>
	<li>Extract probes between the horizons corresponding to the two high-amplitude reflectors. 
	NOTE: There are different tools based on the rendering technique that can help the interpreters better visualize the targets, such as &#34;box probes&#34;, &#34;surfaces probes&#34; and &#34;well probes&#34;. However, for identification of contacts between the sills and encasing strata, the best tool is &#34;surface probe&#34;. (&#34;Surface probe, etc.&#34; are terms in &#39;Petrel&#39; software. The software users should be familiar with these terms).</li>
	<li>Remove the areas surrounding the geological objects of interest by changing the Voxel connectivity opacity threshold value. Set the default threshold value to 20%. The visualization method of &#34;opacity rendering&#34; is used here to display the result of the extraction of basaltic sills ( Figure 2C). 
	NOTE: There are high amplitude reflections along the surface between igneous rock and sedimentary rock because of their significant difference in acoustic impedance. Make the low amplitude parts transparent to highlight the shape of the igneous bodies.</li>
	<li>As the value for isolation can be higher than 20 - 30%, change the value with small increments to make sure all important igneous bodies are not lost; the larger the value, the higher the risk of losing the volume of the real igneous bodies.</li>
	<li>Perform the operation with the provided software.
	<ol>
		<li>Click the Seismic Interpretation pane, click Insert a Horizon Probe. A probe will be added in the geobody interpretation probes tree of input pane. Double click the added horizon probe and a pop-up window will appear.</li>
		<li>Click the Horizons tab in the pop-up window and choose two seismic surfaces that isolate the zone of sills. Click OK to apply the operation.</li>
		<li>Check the newly added probe in the geobody interpretation probes tree shown in the input pane. A seismic cube will then appear in the 3D window.</li>
		<li>Double click the probe and choose the Opacity tab. A histogram of seismic amplitude will be shown in the tab. Use the left mouse button to draw a line in the histogram to control the opacity of the seismic cube. The low amplitude parts of the tube should be invisible and the high amplitude parts will be left.</li>
		<li>Adjust the histogram repeatedly until the desired shape of the interested geobody is achieved.</li>
	</ol>
	</li>
</ol>
4. Extraction of the Feeding Conduits
<ol>
	<li>Choose continuous and high energy reflection horizons at different depths beneath the surface lava flow.</li>
	<li>Do time slicing along the selected horizons, to find out discontinuities corresponding to the vertical conduits.</li>
	<li>Adjust the Two-Way Time (TWT) repeatedly, to achieve the best imaging of the discontinuities of the conduits. 
	NOTE: Seismic data cannot image vertical structures well, so better images from amplitude volumes and variance volumes are chosen by comparing clearness at different travel times.</li>
	<li>Try different slicing techniques, and then choose which can better image the discontinuities. 
	NOTE: Different tools can be used here, such as variance body slicing. Its theoretical basis is the similarity between each seismic section and adjacent seismic traces in the seismic data. Another tool, the variance cube, is a new data body processed by the conventional seismic data, which is helpful for the identification of changes in the structure and lithology, plane combination of the fault, etc.20</li>
	<li>Plot the slices at different travel times or depths into a 3D space.</li>
	<li>Perform the operation with the provided software.
	<ol>
		<li>Double click Volume Attributes in the geophysics tree of the processes pane. Check Structural Methods in the category column and Variance in the attribute column. Select the seismic cube to input box and adjust the other parameter in the parameter tab. For better reading performance, check the box in the realize column. A variance cube is created in the seismic tree of the input pane.</li>
		<li>Right click the variance cube and click Insert Time Slice Intersection to show more horizontal intersections in the 3D window. Use the Manipulate Plane tool in the toolbar of the 3D window to adjust the location of the slices to optimize the display of conduits.</li>
		<li>Right click the seismic amplitude cube and click Insert Time Slice Intersection to show more horizontal intersections in 3D window. Do the same operation as step 4.6.2 to adjust the location of the slices to optimize the display of conduits.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Smallwood, J. R., Maresh, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+properties,+morphology+and+distribution+of+igneous+sills:+modelling,+borehole+data+and+3D+seismic+from+the+Faroe-Shetland+area.">The properties, morphology and distribution of igneous sills: modelling, borehole data and 3D seismic from the Faroe-Shetland area.</a> Geol. Soc. London Spec. Publ. 197 (1), 271-306 (2002).</li><li>Millett, J. M., Hole, M. J., Jolley, D. W., Schofield, N., Campbell, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Frontier+exploration+and+the+North+Atlantic+Igneous+Province:+new+insights+from+a+2.6+km+offshore+volcanic+sequence+in+the+NE+Faroe-Shetland+Basin.">Frontier exploration and the North Atlantic Igneous Province: new insights from a 2.6 km offshore volcanic sequence in the NE Faroe-Shetland Basin.</a> J. Geol. Soc. 173 (2), 320-336 (2016).</li><li>Lee, G. H., Kwon, Y. I., Yoon, C. S., Kim, H. J., Yoo, H. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Igneous+complexes+in+the+eastern+Northern+South+Yellow+Sea+Basin+and+their+implications+for+hydrocarbon+systems.">Igneous complexes in the eastern Northern South Yellow Sea Basin and their implications for hydrocarbon systems.</a> Mar. Pet. Geol. 23 (6), 631-645 (2006).</li><li>Rateau, R., Schofield, N., Smith, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+potential+role+of+igneous+intrusions+on+hydrocarbon+migration,+West+of+Shetland.">The potential role of igneous intrusions on hydrocarbon migration, West of Shetland.</a> Pet. Geosci. 19 (3), 259-272 (2013).</li><li>Magee, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lateral+magma+flow+in+mafic+sill+complexes.">Lateral magma flow in mafic sill complexes.</a> Geosphere. 12 (3), 809-841 (2016).</li><li>Magee, C., Jackson, C. A. L., Schofield, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diachronous+sub-volcanic+intrusion+along+deep-water+margins:+insights+from+the+Irish+Rockall+Basin.">Diachronous sub-volcanic intrusion along deep-water margins: insights from the Irish Rockall Basin.</a> Basin Res. 26 (1), 85-105 (2014).</li><li>Symonds, P., Planke, S., Frey, O., Skogseid, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volcanic+evolution+of+the+Western+Australian+continental+margin+and+its+implications+for+basin+development.">Volcanic evolution of the Western Australian continental margin and its implications for basin development.</a> The sedimentary basins of Western Australia. 2, 33-54 (1998).</li><li>Thomson, K., Hutton, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Geometry+and+growth+of+sill+complexes:+insights+using+3D+seismic+from+the+North+Rockall+Trough.">Geometry and growth of sill complexes: insights using 3D seismic from the North Rockall Trough.</a> BVol. 66 (4), 364-375 (2004).</li><li>Planke, S., Rasmussen, T., Rey, S., Myklebust, R., Dor&#233;, A. G., Vining, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Petroleum Geology: North-West Europe and Global Perspectives-Proceedings of the 6th Petroleum Geology Conference. 6, 833-844 (2005).</li><li>Magee, C., Hunt Stewart, ., E, C. A. L., Jackson, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volcano+growth+mechanisms+and+the+role+of+sub-volcanic+intrusions:+Insights+from+2D+seismic+reflection+data.">Volcano growth mechanisms and the role of sub-volcanic intrusions: Insights from 2D seismic reflection data.</a> Earth Planet. Sci. Lett. 373, 41-53 (2013).</li><li>Schofield, N. J., Brown, D. J., Magee, C., Stevenson, C. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sill+morphology+and+comparison+of+brittle+and+non-brittle+emplacement+mechanisms.">Sill morphology and comparison of brittle and non-brittle emplacement mechanisms.</a> J. Geol. Soc. 169 (2), 127-141 (2012).</li><li>Wang, L., Tian, W., Shi, Y. M., Guan, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volcanic+structure+of+the+Tarim+flood+basalt+revealed+through+3-D+seismological+imaging.">Volcanic structure of the Tarim flood basalt revealed through 3-D seismological imaging.</a> Sci. Bull. 60 (16), 1448-1456 (2015).</li><li>Sun, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neogene+igneous+intrusions+in+the+northern+South+China+Sea:+Evidence+from+high-resolution+three+dimensional+seismic+data.">Neogene igneous intrusions in the northern South China Sea: Evidence from high-resolution three dimensional seismic data.</a> Mar. Pet. Geol. 54, 83-95 (2014).</li><li>Schofield, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seismic+imaging+of+'broken+bridges':+linking+seismic+to+outcrop-scale+investigations+of+intrusive+magma+lobes.">Seismic imaging of 'broken bridges': linking seismic to outcrop-scale investigations of intrusive magma lobes.</a> J. Geol. Soc. 169 (4), 421-426 (2012).</li><li>Thomson, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volcanic+features+of+the+North+Rockall+Trough:+application+of+visualisation+techniques+on+3D+seismic+reflection+data.">Volcanic features of the North Rockall Trough: application of visualisation techniques on 3D seismic reflection data.</a> BVol. 67 (2), 116-128 (2005).</li><li>Jackson, C. A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seismic+reflection+imaging+and+controls+on+the+preservation+of+ancient+sill-fed+magmatic+vents.">Seismic reflection imaging and controls on the preservation of ancient sill-fed magmatic vents.</a> J. Geol. Soc. 169 (5), 503-506 (2012).</li><li>Tian, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Tarim+picrite-basalt-rhyolite+suite,+a+Permian+flood+basalt+from+northwest+China+with+contrasting+rhyolites+produced+by+fractional+crystallization+and+anatexis.">The Tarim picrite-basalt-rhyolite suite, a Permian flood basalt from northwest China with contrasting rhyolites produced by fractional crystallization and anatexis.</a> CoMP. 160 (3), 407-425 (2010).</li><li>Chen, M. -. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peridotite+and+pyroxenite+xenoliths+from+Tarim,+NW+China:+Evidences+for+melt+depletion+and+mantle+refertilization+in+the+mantle+source+region+of+the+Tarim+flood+basalt.">Peridotite and pyroxenite xenoliths from Tarim, NW China: Evidences for melt depletion and mantle refertilization in the mantle source region of the Tarim flood basalt.</a> Lithos. 204, 97-111 (2014).</li><li>Magee, C., Maharaj, S. M., Wrona, T., Jackson, C. A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controls+on+the+expression+of+igneous+intrusions+in+seismic+reflection+data.">Controls on the expression of igneous intrusions in seismic reflection data.</a> Geosphere. 11 (4), 1024-1041 (2015).</li><li>Bahorich, M., Farmer, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3-D+seismic+discontinuity+for+faults+and+stratigraphic+features:+The+coherence+cube.">3-D seismic discontinuity for faults and stratigraphic features: The coherence cube.</a> The Leading Edge. 14 (10), 1053-1058 (1995).</li></ol>

The authors have nothing to disclose.

Here we demonstrate 2 methods for illustrating the morphology and structure of the plumbing system of buried basaltic volcanoes; one is opacity rendering, the other is time slicing.
The opacity rendering method is suitable for geo-bodies that have continuous and near horizontal interfaces with the encasing strata. With this method, one can extract the 3D morphology of magma lobes. Normally, flow directions should be along the long axis of the magma lobes. It is also important that the surface ...

The aim of most of the industrial seismic imaging projects in sedimentary basins is to explore for hydrocarbon reservoirs. In recent years, hydrocarbon exploration has expanded to basins containing large amounts of igneous rocks because many of the volcanogenic basins have considerable oil and gas reservoirs. However, because of the interface of igneous rocks in the volcanogenic basins, seismic data processing presents a series of challenges induced by various intrusions, such as reduced energy transmission, intrinsic attenuation, interference effects, refraction and scattering1. Therefore, oil field companies are focusing their efforts on reducing such a &#34;negative impact&#34; on seismic imaging2,3,4.
Igneous bodies within sedimentary basins are easily identified by two dimensional or 3D seismic reflection imaging due to the large acoustic impedance contrast with the encasing rocks1,5,6. This method can provide spectacular images of both vertical and horizontal structures of the volcanic plumbing systems7,8,9,10,11,12,13. However, the strategies of imaging subsurface volcanos are very different from that of oil and gas explorations8,14,15. This has limited the use of industrial seismic data in studies of subsurface volcanoes, apart from a few successful cases10,15,16. In this paper, we report detailed procedures of seismic data processing, which are customized for interpretation of subsurface volcanoes. We process two seismic cubes, TZ47 and YM2 (Figure 1), to show how to visualize the buried igneous bodies in the Tarim flood basalt17.

<table><tbody><tr><td>The Petrel E&amp;amp;P software platform</td><td>Schlumberger</td><td></td><td>software version:2014</td></tr></tbody></table>

data processing methods for 3d seismic imaging of subsurface volcanoes: applications to the tarim flood basalt

The morphology and structure of plumbing systems can provide key information on the eruption rate and style of basalt lava fields. The most powerful way to study subsurface geo-bodies is to use industrial 3D&#160;reflection seismological imaging. However, strategies to image subsurface volcanoes are very different from that of oil and gas reservoirs. In this study, we process seismic data cubes from the Northern Tarim Basin, China, to illustrate how to visualize sills through opacity rendering techniques and how to image the conduits by time-slicing. In the first case, we isolated probes by the seismic horizons marking the contacts between sills and encasing strata, applying opacity rendering techniques to extract sills from the seismic cube. The resulting detailed sill morphology shows that the flow direction is from the dome center to the rim. In the second seismic cube, we use time-slices to image the conduits, which corresponds to marked discontinuities within the encasing rocks. A set of time-slices obtained at different depths show that the Tarim flood basalts erupted from central volcanoes, fed by separate pipe-like conduits.

We demonstrate the usefulness of the techniques described above by applying them to 2 types of igneous bodies, horizontal sills and vertical volcanic conduits. Extraction of the sills is conducted by using the opaque rendering technique, and interpretation of the volcanic conduit is performed by using slicing technique.
Extraction of sills
Industrial drilling wells have i...

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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Three-dimensional (3D) reflection seismology is a powerful method for imaging subsurface volcanoes. By using industrial 3D seismological data from the Tarim Basin, we illustrate how to extract the sills and the conduits of subsurface volcanoes from seismic data cubes.

The morphology and structure of plumbing systems can provide key information on the eruption rate and style of basalt lava fields. The most powerful way ...

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9.2K Views.  Peking University. Three-dimensional (3D) reflection seismology is a powerful method for imaging subsurface volcanoes. By using industrial 3D seismological data from the Tarim Basin, we illustrate how to extract the sills and the conduits of subsurface volcanoes from seismic data cubes.

Video: Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

A method is described which uses the absence of radiocarbon in industrial chemicals and fuels made from petroleum feedstocks which frequently contaminate the environment. This radiocarbon signal &#8212; or rather the absence of signal &#8212; is evenly distributed throughout a contaminant source pool (unlike an added tracer) and is not impacted by biological, chemical or physical processes (e.g., the 14C radioactive decay rate is immutable). If the fossil-derived contaminant is fully degraded to CO2, a harmless end-product, that CO2 will contain no radiocarbon. CO2 derived from natural organic matter (NOM) degradation will reflect the NOM radiocarbon content (usually &#60;30,000 years old). Given a known radiocarbon content for NOM (a site background), a two end-member mixing model can be used to determine the CO2 derived from a fossil source in a given soil gas or groundwater sample. Coupling the percent CO2 derived from the contaminant with the CO2 respiration rate provides an estimate for the total amount of contaminant degraded per unit time. Finally, determining a zone of influence (ZOI) representing the volume from which site CO2 is collected allows determining the contaminant degradation per unit time and volume. Along with estimates for total contaminant mass, this can ultimately be used to calculate time-to-remediate or otherwise used by site managers for decision-making.

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

A protocol is described wherein CO2 mineralized from organic contaminant (derived from petroleum feedstocks) biodegradation is trapped, quantified, and analyzed for 14C content. A model is developed to determine CO2 capture zone's spatial extent. Spatial and temporal measurements allow integrating contaminant mineralization rates for predicting remediation extent and time.

A method is described which uses the absence of radiocarbon in industrial chemicals and fuels made from petroleum feedstocks which frequently contaminate ...

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and crop management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving plants. X-ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. We aimed to develop a costless and efficient tool that approximates the surface and volume of the root regardless of its shape from three-dimensional (3D) tomography data. The root structure of a Prairie dropseed (Sporobolus heterolepis) specimen was imaged using XCT. The root was reconstructed, and the primary root structure was extracted from the data using a combination of licensed and open-source software. An isosurface polygonal mesh was then created for ease of analysis. We have developed the standalone application imeshJ, generated in MATLAB1, to calculate root volume and surface area from the mesh. The outputs of imeshJ are surface area (in mm2) and the volume (in mm3). The process, utilizing a unique combination of tools from imaging to quantitative root analysis, is described. A combination of XCT and open-source software proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information from the 3D data. This methodology of processing 3D data should be applicable to other material/sample systems where there is connectivity between components of similar X-ray attenuation and difficulties arise with segmentation.

A methodology for obtaining visual and quantitative root structure information from X-ray computed tomography data acquired in-soil is presented.

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to ...

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

We demonstrate the utility of remotely sensed data and the newly developed Software for Assisted Habitat Modeling (SAHM) in predicting invasive species occurrence on the landscape. An ensemble of predictive models produced highly accurate maps of tamarisk (Tamarix spp.) invasion in Southeastern Colorado, USA when assessed with subsequent field validations.

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite ...

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

X-ray microtomography was used to image, at a resolution of 6.6 &#181;m, the pore-scale arrangement of residual carbon dioxide ganglia in the pore-space of a carbonate rock at pressures and temperatures representative of typical formations used for CO2 storage. Chemical equilibrium between the CO2, brine and rock phases was maintained using a high pressure high temperature reactor, replicating conditions far away from the injection site. Fluid flow was controlled using high pressure high temperature syringe pumps. To maintain representative in-situ conditions within the micro-CT scanner a carbon fiber high pressure micro-CT coreholder was used. Diffusive CO2 exchange across the confining sleeve from the pore-space of the rock to the confining fluid was prevented by surrounding the core with a triple wrap of aluminum foil. Reconstructed brine contrast was modeled using a polychromatic x-ray source, and brine composition was chosen to maximize the three phase contrast between the two fluids and the rock. Flexible flow lines were used to reduce forces on the sample during image acquisition, potentially causing unwanted sample motion, a major shortcoming in previous techniques. An internal thermocouple, placed directly adjacent to the rock core, coupled with an external flexible heating wrap and a PID controller was used to maintain a constant temperature within the flow cell. Substantial amounts of CO2 were trapped, with a residual saturation of 0.203 &#177; 0.013, and the sizes of larger volume ganglia obey power law distributions, consistent with percolation theory.

We present a methodology for the imaging of multiple fluid phases at reservoir conditions by the use of x-ray microtomography. We show some representative results of capillary trapping in a carbonate rock sample.

X-ray microtomography was used to image, at a resolution of 6.6 &#181;m, the pore-scale arrangement of residual carbon dioxide ganglia in the pore-space ...

Engineering

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data acquisition times with high spatial resolution. In the electronics industry there is serious interest in performing failure analysis on 3D microelectronic packages, many which contain multiple levels of high-density interconnections. Often in tomography there is a trade-off between image resolution and the volume of a sample that can be imaged. This inverse relationship limits the usefulness of conventional computed tomography (CT) systems since a microelectronic package is often large in cross sectional area 100-3,600 mm2, but has important features on the micron scale. The micro-tomography beamline at the Advanced Light Source (ALS), in Berkeley, CA USA, has a setup which is adaptable and can be tailored to a sample&#39;s properties, i.e., density, thickness, etc., with a maximum allowable cross-section of 36 x 36 mm. This setup also has the option of being either monochromatic in the energy range ~7-43 keV or operating with maximum flux in white light mode using a polychromatic beam. Presented here are details of the experimental steps taken to image an entire 16 x 16 mm system within a package, in order to obtain 3D images of the system with a spatial resolution of 8.7 &#181;m all within a scan time of less than 3 min. Also shown are results from packages scanned in different orientations and a sectioned package for higher resolution imaging. In contrast a conventional CT system would take hours to record data with potentially poorer resolution. Indeed, the ratio of field-of-view to throughput time is much higher when using the synchrotron radiation tomography setup. The description below of the experimental setup can be implemented and adapted for use with many other multi-materials.

For this study synchrotron radiation micro-tomography, a non-destructive three-dimensional imaging technique, is employed to investigate an entire microelectronic package with a cross-sectional area of 16 x 16 mm. Due to the synchrotron&#39;s high flux and brightness the sample was imaged in just 3 min&#160;with an 8.7 &#181;m spatial resolution.

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data ...

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve geologic seals and allow CO2 to escape. However, the dissolution processes at reservoir conditions are poorly understood. Thus, time-resolved experiments are needed to observe and predict the nature and rate of dissolution at the pore scale. Synchrotron fast tomography is a method of taking high-resolution time-resolved images of complex pore structures much more quickly than traditional &#181;-CT. The Diamond Lightsource Pink Beam was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 hours. The images were segmented and the porosity and permeability were measured using image analysis and network extraction. Porosity increased uniformly along the length of the sample; however, the rate of increase of both porosity and permeability slowed at later times.

Synchrotron fast tomography was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 h.

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve ...

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Landscape processes are critical components of soil formation and play important roles in determining soil properties and spatial structure in landscapes. We propose a new approach using stepwise principal component regression to predict soil redistribution and soil organic carbon across various spatial scales.

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it ...

Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

An experimental method is presented in this paper to facilitate visualization of the detailed flow fields and determination of the near-boundary shear and normal stresses within an equilibrium scour hole induced by a vibrating pipeline. This method involves the implementation of a pipeline vibration system in a straight flume, a time-resolved particle image velocimetry (PIV) system for pipeline displacement tracking and flow fields measurements. The displacement time-series of the vibrating pipeline are obtained by using the cross-correlation algorithms. The steps for processing raw particle laden images obtained by using the time-resolved PIV are described. The detailed instantaneous flow fields around the vibrating pipeline at different vibrating phases are calculated by using a multiple-time-interval cross-correlation algorithm to avoid displacement bias error in the flow regions with a large velocity gradient. By applying the wavelet transform technique, the captured images that have the same vibrating phase are accurately cataloged before the phase-averaged velocity fields are obtained. The key advantages of the flow measurement technique described in this paper are that it has a very high temporal and spatial resolution and can be simultaneously used to obtain the pipeline dynamics, flow fields, and near-boundary flow stresses. By using this technique, more in-depth studies of the 2-dimensional flow field in a complex environment, such as that around a vibrating pipeline, can be conducted to better understand the associated sophisticated scour mechanism.

The goal of the protocol is to enable visualization of the detailed flow fields and determination of the near-boundary shear and normal stresses within an equilibrium scour hole induced by a vibrating pipeline.

An experimental method is presented in this paper to facilitate visualization of the detailed flow fields and determination of the near-boundary shear and ...

A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry

Structure-from-motion (SfM) photogrammetry is a technique used to generate three-dimensional (3D) reconstructions from a sequence of two-dimensional (2D) images. SfM methods are becoming increasingly popular as a noninvasive way to monitor many systems, including anthropogenic and natural landscapes, geologic structures, and both terrestrial and aquatic ecosystems. Here, a detailed protocol is provided for collecting SfM imagery to generate 3D models of benthic habitats. Additionally, the cost, time efficiency, and output quality of employing a Digital Single Lens Reflex (DSLR) camera versus a less expensive action camera have been compared. A tradeoff between computational time and resolution was observed, with the DSLR camera producing models with more than twice the resolution, but taking approximately 1.4-times longer to produce than the action camera. This primer aims to provide a thorough description of the steps necessary to collect SfM data in benthic habitats for those who are unfamiliar with the technique as well as for those already using similar methods.

We provide a detailed protocol for conducting underwater structure-from-motion photogrammetry surveys to generate 3D models and orthomosaics.

Structure-from-motion (SfM) photogrammetry is a technique used to generate three-dimensional (3D) reconstructions from a sequence of two-dimensional (2D) ...

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

In situ wettability measurements in hydrocarbon reservoir rocks have only been possible recently. The purpose of this work is to present a protocol to characterize the complex wetting conditions of hydrocarbon reservoir rock using pore-scale three-dimensional X-ray imaging at subsurface conditions. In this work, heterogeneous carbonate reservoir rocks, extracted from a very large producing oil field, have been used to demonstrate the protocol. The rocks are saturated with brine and oil and aged over three weeks at subsurface conditions to replicate the wettability conditions that typically exist in hydrocarbon reservoirs (known as mixed-wettability). After the brine injection, high-resolution three-dimensional images (2 &#181;m/voxel) are acquired and then processed and segmented. To calculate the distribution of the contact angle, which defines the wettability, the following steps are performed. First, fluid-fluid and fluid-rock surfaces are meshed. The surfaces are smoothed to remove voxel artefacts, and in situ contact angles are measured at the three-phase contact line throughout the whole image. The main advantage of this method is its ability to characterize in situ wettability accounting for pore-scale rock properties, such as rock surface roughness, rock chemical composition, and pore size. The in situ wettability is determined rapidly at hundreds of thousands of points. 
The method is limited by the segmentation accuracy and X-ray image resolution. This protocol could be used to characterize the wettability of other complex rocks saturated with different fluids and at different conditions for a variety of applications. For example, it could help in determining the optimal wettability that could yield an extra oil recovery (i.e., designing brine salinity accordingly to obtain higher oil recovery) and to find the most efficient wetting conditions to trap more CO2 in subsurface formations.

This protocol is presented to characterize the complex wetting conditions of an opaque porous medium (hydrocarbon reservoir rock) using three-dimensional images obtained by X-ray microtomography at subsurface conditions.

In situ wettability measurements in hydrocarbon reservoir rocks have only been possible recently. The purpose of this work is to present a protocol to ...