@inproceedings{ding_k-means_2004,
	title = {K-means clustering via principal component analysis},
	url = {http://dl.acm.org/citation.cfm?id=1015408},
	urldate = {2016-03-30},
	booktitle = {Proceedings of the twenty-first international conference on {Machine} learning},
	publisher = {ACM},
	author = {Ding, Chris and He, Xiaofeng},
	year = {2004},
	pages = {29},
	file = {icml2_format1.dvi - KmeansPCA1.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/B63URTJ4/KmeansPCA1.pdf:application/pdf}
}

@inproceedings{zhang_birch:_1996,
	title = {{BIRCH}: an efficient data clustering method for very large databases},
	volume = {25},
	shorttitle = {{BIRCH}},
	url = {http://dl.acm.org/citation.cfm?id=233324},
	urldate = {2016-02-24},
	booktitle = {{ACM} {Sigmod} {Record}},
	publisher = {ACM},
	author = {Zhang, Tian and Ramakrishnan, Raghu and Livny, Miron},
	year = {1996},
	pages = {103--114},
	file = {zhang96.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/7XT4CRAC/zhang96.pdf:application/pdf}
}

@incollection{scholkopf_kernel_1997,
	title = {Kernel principal component analysis},
	url = {http://link.springer.com/chapter/10.1007/BFb0020217},
	urldate = {2016-02-24},
	booktitle = {Artificial {Neural} {Networks}—{ICANN}'97},
	publisher = {Springer},
	author = {Schölkopf, Bernhard and Smola, Alexander and Müller, Klaus-Robert},
	year = {1997},
	pages = {583--588},
	file = {scholkopf_kernel.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/CWJX7F65/scholkopf_kernel.pdf:application/pdf}
}

@article{shuey_simplification_1985,
	title = {A simplification of the {Zoeppritz} equations},
	volume = {50},
	url = {http://geophysics.geoscienceworld.org/content/50/4/609.abstract},
	doi = {10.1190/1.1441936},
	abstract = {The compressional wave reflection coefficient R(theta ) given by the Zoeppritz equations is simplified to the following:EquationThe first term gives the amplitude at normal incidence (theta = 0), the second term characterizes R(theta ) at intermediate angles, and the third term describes the approach to critical angle. The coefficient of the second term is that combination of elastic properties which can be determined by analyzing the offset dependence of event amplitude in conventional multichannel reflection data. If the event amplitude is normalized to its value for normal incidence, then the quantity determined isEquationA 0 specifies the normal, gradual decrease of amplitude with offset; its value is constrained well enough that the main information conveyed is Delta sigma /R 0 , where Delta sigma is the contrast in Poisson's ratio at the reflecting interface and R 0 is the amplitude at normal incidence. This simplified formula for R(theta ) accounts for all of the relations between R(theta ) and elastic properties first described by Koefoed in 1955.},
	number = {4},
	journal = {Geophysics},
	author = {Shuey, R. T.},
	year = {1985},
	pages = {609--614},
	file = {A simplification of the Zoeppritz equations - 1.1441936:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/ZG3232CK/1.pdf:application/pdf}
}

@article{castagna_framework_1998,
	title = {Framework for {AVO} gradient and intercept interpretation},
	volume = {63},
	url = {http://geophysics.geoscienceworld.org/content/63/3/948.abstract},
	doi = {10.1190/1.1444406},
	abstract = {Amplitude variation with offset (AVO) interpretation may be facilitated by crossplotting the AVO intercept (A) and gradient (B). Under a variety of reasonable petrophysical assumptions, brine-saturated sandstones and shales follow a well-defined “background” trend in the A-B plane. Generally, A and B are negatively correlated for “background” rocks, but they may be positively correlated at very high VP/VS ratios, such as may occur in very soft shallow sediments. Thus, even fully brine-saturated shallow events with large reflection coefficients may exhibit large increases in AVO.Deviations from the background trend may be indicative of hydrocarbons or lithologies with anomalous elastic properties. However, in contrast to the common assumptions that gas-sand amplitude increases with offset, or that the reflection coefficient becomes more negative with increasing offset, gas sands may exhibit a variety of AVO behaviors. A classification of gas sands based on location in the A-B plane, rather than on normal-incidence reflection coefficient, is proposed. According to this classification, bright-spot gas sands fall in quadrant III and have negative AVO intercept and gradient. These sands exhibit the amplitude increase versus offset which has commonly been used as a gas indicator. High-impedance gas sands fall in quadrant IV and have positive AVO intercept and negative gradient. Consequently, these sands initially exhibit decreasing AVO and may reverse polarity. These behaviors have been previously reported and are addressed adequately by existing classification schemes. However, quadrant II gas sands have negative intercept and positive gradient. Certain “classical” bright spots fall in quadrant II and exhibit decreasing AVO. Examples show that this may occur when the gas-sand shear-wave velocity is lower than that of the overlying formation. Common AVO analysis methods such as partial stacks and product (A × B) indicators are complicated by this nonuniform gas-sand behavior and require prior knowledge of the expected gas-sand AVO response. However, Smith and Gidlow's (1987) fluid factor, and related indicators, will theoretically work for gas sands in any quadrant of the A-B plane.},
	number = {3},
	journal = {Geophysics},
	author = {Castagna, John P. and Swan, Herbert W. and Foster, Douglas J.},
	year = {1998},
	pages = {948--956},
	file = {Framework for AVO gradient and intercept interpretation - framework for AVO interpretation.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/3TRIGWV8/framework for AVO interpretation.pdf:application/pdf}
}

@article{castagna_relationships_1985,
	title = {Relationships between compressional-wave and shear-wave velocities in clastic silicate rocks},
	volume = {50},
	url = {http://geophysics.geoscienceworld.org/content/50/4/571.abstract},
	doi = {10.1190/1.1441933},
	abstract = {New velocity data in addition to literature data derived from sonic log, seismic, and laboratory measurements are analyzed for clastic silicate rocks. These data demonstrate simple systematic relationships between compressional and shear wave velocities. For water-saturated clastic silicate rocks, shear wave velocity is approximately linearly related to compressional wave velocity and the compressional-to-shear velocity ratio decreases with increasing compressional velocity. Laboratory data for dry sandstones indicate a nearly constant compressional-to-shear velocity ratio with rigidity approximately equal to bulk modulus. Ideal models for regular packings of spheres and cracked solids exhibit behavior similar to the observed water-saturated and dry trends. For dry rigidity equal to dry bulk modulus, Gassmann's equations predict velocities in close agreement with data from the water-saturated rock.},
	number = {4},
	journal = {Geophysics},
	author = {Castagna, J. P. and Batzle, M. L. and Eastwood, Raymond L.},
	year = {1985},
	pages = {571--581},
	file = {Relationships between compressional-wave and shear-wave velocities in clastic silicate rocks - GPY00571.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/BUGMSPJR/GPY00571.pdf:application/pdf}
}

@inproceedings{martin_marmousi-2:_2002,
	title = {Marmousi-2: an updated model for the investigation of {AVO} in structurally complex areas},
	shorttitle = {Marmousi-2},
	url = {https://www.onepetro.org/conference-paper/SEG-2002-1979},
	urldate = {2016-03-30},
	booktitle = {2002 {SEG} {Annual} {Meeting}},
	publisher = {Society of Exploration Geophysicists},
	author = {Martin, Gary S. and Larsen, Shawn and Marfurt, Kurt and {others}},
	year = {2002},
	file = {Microsoft Word - 3CB39886-41E4-E4CC.doc - SEG-2002-1979:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/E572GN3B/SEG-2002-1979.pdf:application/pdf}
}

@article{sava_angledomain_2003,
	title = {Angle domain common image gathers by wavefield extrapolation},
	volume = {68},
	language = {en},
	number = {3},
	urldate = {2016-03-30},
	journal = {GEOPHYSICS},
	author = {Sava, Paul and Fomel, Sergei},
	year = {2003},
	pages = {1065--1074},
}

@article{gajewski_amplitude_2002,
	title = {Amplitude preserving {Kirchhoff} migration: a traveltime based strategy},
	volume = {46},
	shorttitle = {Amplitude preserving {Kirchhoff} migration},
	url = {http://link.springer.com/article/10.1023/A:1019849919186},
	number = {2},
	urldate = {2016-03-30},
	journal = {Studia geophysica et geodaetica},
	author = {Gajewski, Dirk and Coman, Radu and Vanelle, Claudia},
	year = {2002},
	pages = {193--211},
	file = {Amplitude Preserving Kirchhoff Migration\: A Traveltime Based Strategy - art%3A10.1023%2FA%3A1019849919186.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/NCV37MXD/art%3A10.1023%2FA%3A1019849919186.pdf:application/pdf}
}

@article{zhang_amplitude-preserving_2014,
	title = {Amplitude-preserving reverse time migration: {From} reflectivity to velocity and impedance inversion},
	volume = {79},
	url = {http://geophysics.geoscienceworld.org/content/79/6/S271.abstract},
	doi = {10.1190/geo2013-0460.1},
	abstract = {Conventional methods of prestack depth imaging aim at producing a structural image that delineates the interfaces of the geologic variations or the reflectivity of the earth. However, it is the underlying impedance and velocity changes that generate this reflectivity that are of more interest for characterizing the reservoir. Indeed, the need to generate a better product for geologic interpretation leads to the subsequent application of traditional seismic-inversion techniques to the reflectivity sections that come from typical depth-imaging processes. The drawback here is that these seismic-inversion techniques use additional information, e.g., from well logs or velocity models, to fill the low frequencies missing in traditional seismic data due to the free-surface ghost in marine acquisition. We found that with the help of broadband acquisition and processing techniques, the bandwidth gap between the depth-imaging world and seismic inversion world is reducing. We outlined a theory that shows how angle-domain common-image gathers produced by an amplitude-preserving reverse time migration can estimate impedance and velocity perturbations. The near-angle stacked image provides the impedance perturbation estimate whereas the far-angle image can be used to estimate the velocity perturbation. In the context of marine acquisition and exploration, our method can, together with a ghost compensation technique, be a useful tool for seismic inversion, and it is also adaptable to a full-waveform inversion framework. We developed synthetic and real data examples to test that the method is reliable and provides additional information for interpreting geologic structures and rock properties.},
	number = {6},
	journal = {Geophysics},
	author = {Zhang, Yu and Ratcliffe, Andrew and Roberts, Graham and Duan, Lian},
	year = {2014},
	pages = {S271--S283},
	file = {2013-0460 271..283 - S271.full.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/MMN3SMNQ/S271.full.pdf:application/pdf}
}

@article{sava_amplitude-preserved_2001,
	title = {Amplitude-preserved common image gathers by wave-equation migration},
	url = {http://library.seg.org/doi/pdf/10.1190/1.1816598},
	urldate = {2016-03-30},
	journal = {71st Ann. Internat. Mtg: Soc. of Expl. Geophys},
	author = {Sava, Paul and Biondi, Biondo and Fomel, Sergey and {others}},
	year = {2001},
	pages = {296--299},
	file = {pcs_seg01.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/5MGP7JKX/pcs_seg01.pdf:application/pdf}
}

@article{hofmann_kernel_2008,
	title = {Kernel methods in machine learning},
	volume = {36},
	issn = {0090-5364},
	url = {http://projecteuclid.org/euclid.aos/1211819561},
	doi = {10.1214/009053607000000677},
	language = {en},
	number = {3},
	urldate = {2016-03-31},
	journal = {The Annals of Statistics},
	author = {Hofmann, Thomas and Schölkopf, Bernhard and Smola, Alexander J.},
	year = {2008},
	pages = {1171--1220},
	file = {Kernel methods in machine learning - 0701907.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/HI6VPIR8/0701907.pdf:application/pdf}
}

@article{scheevel_principal_2001,
	title = {Principal component analysis applied to 3D seismic data for reservoir property estimation},
	volume = {4},
	url = {https://www.onepetro.org/journal-paper/SPE-69739-PA},
	number = {01},
	urldate = {2016-03-31},
	journal = {SPE Reservoir Evaluation \& Engineering},
	author = {Scheevel, J. R. and Payrazyan, K. and {others}},
	year = {2001},
	pages = {64--72},
	file = {for_publication_SPE_56734.PDF - SPE_56734_Scheevel_Payrazyan.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/P9MCABTJ/SPE_56734_Scheevel_Payrazyan.pdf:application/pdf}
}

@article{hagen_application_1982,
	title = {The application of principal components analysis to seismic data sets},
	volume = {20},
	url = {http://www.sciencedirect.com/science/article/pii/0016714282900096},
	number = {1},
	urldate = {2016-03-31},
	journal = {Geoexploration},
	author = {Hagen, David C.},
	year = {1982},
	pages = {93--111},
	file = {PII\: 0016-7142(82)90009-6 - 1-s2.0-0016714282900096-main.pdf:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/RG8DEXM2/1-s2.0-0016714282900096-main.pdf:application/pdf}
}

@inproceedings{hami-eddine_anomaly_2012,
	address = {SEG},
	title = {Anomaly {Detection} {Using} {Dynamic} {Neural} {Networks}, {Classi}?cation of {Prestack} {Data}},
	abstract = {SUMMARYAutomatic seismic facies classification is now common practice in the oil and gas industry. Unfortunately unsupervised seismic classification is often not optimal. The main criticism of unsupervised classification is the a priori nature of the seismic data set organization and the poor description of seismic due to data redundancy. Data reduction, such as Principal Component Analysis (PCA) is often used in association to reveal the principal characteristics of the geological system. The new clustering described here will with a dynamic process naturally search to fill the data space, and to describe the full variability of the seismic. The process can be imagined as a gas expanding in volume. Finally, the process details the anomalies which potentially correspond to hydrocarbon accumulations.},
	booktitle = {{SEG}-2012-1222},
	publisher = {Society of Exploration Geophysicists},
	author = {Hami-Eddine, Kamal and Klein, Pascal and Richard, Loic and Furniss, Andrew},
	year = {2012},
	file = {Anomaly detection using dynamic neural networks, classification of prestack data - SEG-2012-1222:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/RWXIKRP6/SEG-2012-1222.pdf:application/pdf}
}

@inproceedings{saleh_avo_2000,
	title = {{AVO} attribute extraction via principal component analysis},
	url = {https://www.onepetro.org/conference-paper/SEG-2000-0126},
	urldate = {2016-03-31},
	booktitle = {2000 {SEG} {Annual} {Meeting}},
	publisher = {Society of Exploration Geophysicists},
	author = {Saleh, Saad J. and de Bruin, Jan A. and {others}},
	year = {2000},
	file = {AVO attribute extraction via principal component analysis - SEG-2000-0126:/Volumes/Users/bbougher/Library/Application Support/Firefox/Profiles/x78fp12z.default/zotero/storage/PSTEZ5FM/SEG-2000-0126.pdf:application/pdf}
}