From data conditioning, depth imaging and reservoir characterization to machine learning

References

1. AdilettaS., HolfR., KabaA., GiminezL., KosterK. and VanDe Couvering N.
   [2019]. The role of geophysics in Oxy’s Permian basin unconventional resource play appraisal and development workflow. First Break, 37 (3), 45–52.
   [Google Scholar]
2. Alkhalifah, T.
   [2014]. Full waveform inversion in an anisotropic world; where are the parameters hiding?EAGE, Houten, The Netherlands.
   [Google Scholar]
3. Alkhalifah, T. and Plessix R.
   [2014]. A recipe for practical full-waveform inversion in anisotropic media: An analytical parameter resolution study. Geophysics,79 (3), R91–R101
   [Google Scholar]
4. Aminzadeh, F. and De Groot, P.
   [2004]. Soft computing for qualitative and quantitative seismic object and reservoir property prediction. Part 1: Neural network applications. First Break, 22 (3), 49–54.
   [Google Scholar]
5. Aminzadeh, F. and Wilkinson, D.
   [2004]. Soft computing for qualitative and quantitative seismic object and reservoir property prediction. Part 2: Fuzzy Logic applications. First Break, 22 (4), 69–78.
   [Google Scholar]
6. Avseth, P., Mukerji, T. and Mavko, G.
   [2005]. Quantitative seismic interpretation, applying rock physics tools to reduce interpretation risk. Cambridge University Press.
   [Google Scholar]
7. Bachir, A. and Quenes, A.
   [2019] Physics-guided neural networks for predicting unconventional well performance- using unconventional rate transient analysis for smarter production analytics. First Break, 37 (9), 73–75
   [Google Scholar]
8. Balz, O., Pivot, F. and Veeken, P.C.H
   [1999]. Reservoir characterisation using neural networks controlled by petrophysical and seismic modelling. 61st EAGE annual meeting, Glasgow, Extended abstracts, S015.
   [Google Scholar]
9. Beller, M., Chaouch, N., Petri, V., Veeken, P., Landa, E., Kokoshin, E., Smirnov, K. and Paleari, C.
   , [2019]. Diffraction Imaging: resolving subtle seismic geo-features in the Rembrandt and Vermeer Chalk Fields, Dutch Offshore Block F17. 81th EAGE annual Conference and Exhibition, Extended Abstracts.
   [Google Scholar]
10. Belova, A.Y., Gurevich, D.V., Bashkeev, A.S, Davydenko, Y.A. and Veeken, P.
    [2020]. Mineral prospecting for buried copper-molybdene ores in northern Kazakhstan using electromagnetic sensing and induced polarisation technology (EMS-IP). 82th EAGE annual conference and exhibition, Extended Abstracts.
    [Google Scholar]
11. Borghi, P., Curia, D., Alayon, M., Veeken, P., Lescano, I. and Justo, D.
    [2017]. Sierra de Reyes 3D seismic survey (onshore Argentina): depth imaging complex geology by applying Multifocusing, Kirchhoff, Beam and RTM workflows. First Break, 35 (12), 67–76.
    [Google Scholar]
12. Buijs, H., Ponce, J. and Veeken, P.
    [2019]. Validation of flow capacity and state-of-stress models in unconventional reservoirs by the implementation of numerical models of diagnostic fracture injection tests. The Leading Edge, 38 (6), 306–314.
    [Google Scholar]
13. Chopra, S. and Marfurt, K.J.
    [2006]. Seismic attribute mapping of structure and stratigraphy. EAGE DISC handout.
    [Google Scholar]
14. Chopra, S. and Marfurt, K.J.
    [2007]. Seismic attributes for prospect identification and reservoir characterisation. Geophysical developments 11, SEG, Tulsa, USA.
    [Google Scholar]
15. Colombo, D. and De Stefano, M.
    [2007]. Geophysical modeling via simultaneous joint inversion of seismic, gravity, and electromagnetic data: Application to prestack depth imaging. The Leading Edge, 26, 326–331.
    [Google Scholar]
16. CottonJ.C., ForguesE. and MeunierJ.
    [2013]. Continuous land seismic reservoir monitoring of thermal EOR in the Netherlands. 75th EAGE Conference & Exhibition, Extended Abstracts.
    [Google Scholar]
17. Curia, D., Veeken, P., Zunino, J., Deev, K. and Pelman, D.
    [2012]. Multifocusing seismic processing to improve poor response areas below basalt layers, Cañadon Asfalto Basin (Argentina). 74th EAGE Conference & Exhibition, Extended Abstracts.
    [Google Scholar]
18. Curia, D., Veeken, P., Justo, D. and Alayon, M.
    [2018]. Anisotropic wide azimuth 3D seismic data for an unconventional shale oil project, Aguada Federal Block, NW Argentina. 80th EAGE Annual Conference and Exhibition, Extended Abstracts, WE B14.
    [Google Scholar]
19. Curia, D. and Veeken, P.
    [2019]. Estimating rock physical parameters using anisotropic 3D seismic data to characterise unconventional Vaca Muerta oil shale deposits in the Neuquen Basin, western Argentina. First Break, 37 (11).
    [Google Scholar]
20. CuriaD.
    , R.Elia and P.Veeken [2020]. Multicomponent 3D-3C data acquisition and processing in the Bandurria Norte concession, Neuquén Basin, Argentina. 82th EAGE Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
21. DagallierG., MalartreF., LaitinenA., VanCampenhout I.P.A.M and VeekenP.C.H.
    [1999]. Ground Penetrating Radar application in a shallow marine Oxfordian limestone sequence located on the eastern flank of the Paris Basin, NE France. Sedimentary Geology, 130, 149–165.
    [Google Scholar]
22. Da Silva, M., Rauch, M., Soto Cuervo, A. and Veeken, P.C.H.
    [2004a]. Data conditioning for a combined inversion and AVO reservoir characterisation study. 60th Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
23. Dubrule, O.
    [2003]. Geostatistics for seismic data integration in earth models. EAGE distinguished instructor series, 6, 282.
    [Google Scholar]
24. Eiken, O., Stenvold, T. & Zumberge, M. and Alnes, H. and Sasagawa, G.
    [2008]. Gravimetric monitoring of gas production from the Troll field. Geophysics, 73. WA149–154, Doi:10.1190/1.2978166.
    https://doi.org/10.1190/1.2978166 [Google Scholar]
25. Gierse, G., Pruesmann, J., Laggiard, E., Boennemann, C. and Meyer, H.
    [2003]. Improved imaging of 3D marine seismic data from offshore Costa Rica with CRS processing. First Break,21 (12), 45–49.
    [Google Scholar]
26. Gisolf, D., Huis in’t Veld, R., Haffinger, P., Hanitzsch, C., Doulgeris, P. and Veeken, P.
    [2014]. Non-linear Full Wavefield Inversion applied to Carboniferous reservoirs in the Wingate gasfield (Southern North Sea, offshore UK). 76th EAGE Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
27. Guilbot, J., Grausem, M. and Pichon, P.L.
    [1996]. Lithology classification using seismic impedance, Bongkot field, Gulf of Thailand. 59th EAGE Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
28. Koren, Z. and Ravve, I.
    [2011]. Full-azimuth subsurface angle domain wavefield decomposition and imaging, Part I: Directional and reflection image gathers. Geophysics, 76, P.S1–S13.
    [Google Scholar]
29. Landa, E., Litvykova, O., Kokoshin, E., Esinov, B. and Paleari, C.
    [2019]. Common Reflection Angle Migration, an emerging, ray-based, seismic depth migration offers flexible imaging solutions, to resolve subtle subsurface geofeatures in complex geological settings. Geo, 32–36.
    [Google Scholar]
30. Leal, J., Jeronimo, R., Rada, F., Viloria, R., and Roden, R.
    [2019]. Net reservoir discrimination through multi-attribute analysis at single sample scale. First Break, 37 (9), 77–86.
    [Google Scholar]
31. Mantilla, A., Szavian, P., Bell, R. and Han, C.
    [2019]. Integrated reservoir characterisation using high definition frequency decomposition, multi-attribute analysis and forward modelling, Chandon discovery, Australia. First Break, 37 (3), 65–74.
    [Google Scholar]
32. Marsala, A.F., Al-Buali, M., Ali, Z., Ma, S.M., He, Z., Biyan, T., Zhao, G. and He, T.
    [2011]. First borehole to surface electromagnetic survey in KSA: Reservoir mapping and monitoring at a new scale. 81st Annual International Meeting, SEG, Expanded Abstracts, 1364–1372.
    [Google Scholar]
33. Odegaard, E. and Avseth, P.
    [2004]. Well log and seismic data analysis using rock physics templates. First Break, 22 (10), 37–43.
    [Google Scholar]
34. Priezzhev, I.I., Veeken, P.C.H., Egorov, S.V., Nikiforov, A.N. and Strecker, U.
    [2019a]. Seismic waveform classification based on Kohonen 3D neural networks with RGB visualisation. First Break, 37, 37–43.
    [Google Scholar]
35. Priezzhev, I.I., Danko, D.A. Veeken, P.C.H. Strecker, U. and Nikiforov, A.N.
    [2019b]. New high-resolution discontinuity seismic attribute based on DTW (Dynamic Time Warping) algorithm. 81th EAGE annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
36. Priezzhev, I.I., Danko, D.A., Strecker, U. and Veeken, P.C.H.
    [2020]. A new, higher-resolution, multi-trace seismic discontinuity attribute based on a Dynamic Time Warping algorithm. First Break, 38 (4), 6.
    [Google Scholar]
37. Rowbotham, P.S., Marion, D., Lamy, P., Insalaco, E., Swaby, P.A. and Boisseau, Y.
    [2003]. Multi-disciplinary stochastic impedance inversion: integrating geological understanding and capturing reservoir uncertainty. Petroleum Geoscience, 9, 287–294.
    [Google Scholar]
38. Schulz, P.
    [1999]. The seismic velocity model as an interpretation asset. SEG/EAGE short course 2, Abstracts.
    [Google Scholar]
39. Tietze, K., Ritter, O., Patzer, C., Veeken, P. and Verboom, B.
    [2017]. Borehole CSEM for HC-Saturation Monitoring in the Bockstedt Oilfield (Onshore NW Germany). SPE Reservoir Evaluation and Engineering, Doi: 10.2118/183165‑PA.
    https://doi.org/10.2118/183165-PA [Google Scholar]
40. Thomsen, L.
    [2002]. Understanding seismic anisotropy in exploration and exploitation. Distinguished instructor series, 5, Doi: 10.1190/1.9781560801986..
    https://doi.org/10.1190/1.9781560801986 [Google Scholar]
41. Torres-Verdin, C., Victoria, M., Merletti, G. and Pendrel, J.
    [1999]. Trace-based and geostatistical inversion of 3-D seismic data for thin sand delineation: An application in San Jorge Basin, Argentina. The Leading Edge, 18 (9), 1070–1077.
    [Google Scholar]
42. Veeken, P.C.H.
    [2007]. Seismic stratigraphy, basin analysis and reservoir characterisation. In: K.Helbig and S.Treitel (Eds.) Handbook of Geophysical Exploration, 37, Elsevier, Amsterdam, The Netherlands.
    [Google Scholar]
43. Veeken, P.C.H.
    [2019]. Benefits of joint seismic and EM inversion for hydrocarbon development projects. 81st EAGE Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
44. Veeken, P., Legeydo, P., Davidenko, Y., Kudryavceva, E., Ivanov, S. and Chuvaev, A.
    [2009a]. Benefits of the induced polarisation geo-electric method to exploration of hydrocarbon prospects. Geophysics, 74 (2), B47–59.
    [Google Scholar]
45. Veeken, P., Priezzhev, I., Shmaryan, L., Shteyn, Y., Barkov, A. and Ampilov, Y.
    [2009b]. 3D non-linear multi-trace genetic inversion applied on seismic data across the Shtokman field (offshore northern Russia). Geophysics, 74 (6), WCD 49–59.
    [Google Scholar]
46. Veeken, P.C.H. and Van Moerkerken, B.
    [2013]. Seismic stratigraphy and depositional facies models. EAGE Publications, Houten, The Netherlands.
    [Google Scholar]
47. Veeken, P., Dillen, M., Tietze, K., Patzer C. and Ritter, O.
    [2019]. Resistivity and reservoir monitoring in the Lower Cretaceous Bockstedt oilfield using a borehole CSEM setup. 81st Annual International Conference and Exhibition, Extended Abstracts.
    [Google Scholar]
48. Veeken, P.C.H., Kashubin, A., Curia, D., Davydenko, Y. and Priezzhev, I.
    [2020]. Optimising the geoscience workflow: data conditioning, depth imaging, reservoir characterisation and machine learnings. 82nd EAGE Annual Conference and Exhibition, Extended Abstracts.
    [Google Scholar]