Rock Typing and Characterization of Carbonate Reservoirs

2012 ◽  
Author(s):  
Prasanta Kumar Mishra ◽  
Abdulrahman Al-Harthy ◽  
Jasem M. Al-Kanderi ◽  
Muatasam Al-Raisi ◽  
Ghaliah Al-Alawi ◽  
...  
Keyword(s):  
Carbonate Reservoirs ◽  
Rock Typing

A Machine Learning Methodology for Rock-Typing Using Relative Permeability Curves

2021 ◽  
Author(s):  
Carlos Esteban Alfonso ◽  
Frédérique Fournier ◽  
Victor Alcobia
Keyword(s):  
Machine Learning ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
Fractional Flow ◽  
Flow Curves ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Permeability Data

Abstract The determination of the petrophysical rock-types often lacks the inclusion of measured multiphase flow properties as the relative permeability curves. This is either the consequence of a limited number of SCAL relative permeability experiments, or due to the difficulty of linking the relative permeability characteristics to standard rock-types stemming from porosity, permeability and capillary pressure. However, as soon as the number of relative permeability curves is significant, they can be processed under the machine learning methodology stated by this paper. The process leads to an automatic definition of relative permeability based rock-types, from a precise and objective characterization of the curve shapes, which would not be achieved with a manual process. It improves the characterization of petrophysical rock-types, prior to their use in static and dynamic modeling. The machine learning approach analyzes the shapes of curves for their automatic classification. It develops a pattern recognition process combining the use of principal component analysis with a non-supervised clustering scheme. Before this, the set of relative permeability curves are pre-processed (normalization with the integration of irreducible water and residual oil saturations for the SCAL relative permeability samples from an imbibition experiment) and integrated under fractional flow curves. Fractional flow curves proved to be an effective way to unify the relative permeability of the two fluid phases, in a unique curve that characterizes the specific poral efficiency displacement of this rock sample. The methodology has been tested in a real data set from a carbonate reservoir having a significant number of relative permeability curves available for the study, in addition to capillary pressure, porosity and permeability data. The results evidenced the successful grouping of the relative permeability samples, according to their fractional flow curves, which allowed the classification of the rocks from poor to best displacement efficiency. This demonstrates the feasibility of the machine learning process for defining automatically rock-types from relative permeability data. The fractional flow rock-types were compared to rock-types obtained from capillary pressure analysis. The results indicated a lack of correspondence between the two series of rock-types, which testifies the additional information brought by the relative permeability data in a rock-typing study. Our results also expose the importance of having good quality SCAL experiments, with an accurate characterization of the saturation end-points, which are used for the normalization of the curves, and a consistent sampling for both capillary pressure and relative permeability measurements.

Sequence Stratigraphy and Characterization of Carbonate Reservoirs: SEPM Short Course Notes no. 40

Palaios ◽  
1998 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
J. Fred Read ◽  
Charles Kerans ◽  
Scott Tinker
Keyword(s):  
Sequence Stratigraphy ◽  
Carbonate Reservoirs ◽  
Short Course

Ultra-deepwater seismic plays offshore Brazil — Future drilling off Santos and Campos Basins

2019 ◽  
Vol 7 (4) ◽  
pp. SH99-SH109
Author(s):  
Roberto Fainstein ◽  
Ana Krueger ◽  
Webster Ueipass Mohriak
Keyword(s):  
Data Acquisition ◽  
Reservoir Characterization ◽  
Carbonate Reservoirs ◽  
Source Rocks ◽  
Brazilian Coast ◽  
Depth Migration ◽  
3D Data ◽  
Shelf Slope ◽  
Seismic Amplitudes

Contemporaneous seismic data acquisition in the Santos and Campos Basins offshore Brazil have focused on image characterization of deepwater and ultra-deepwater reservoirs and their relationship with hydrocarbons originating from synrift source rocks. Our interpretation has mapped the stratigraphy of postsalt turbidite reservoirs, and, on the presalt lithology, it has uncovered the underlying synrift sequences that embrace oil-bearing source rocks and the prolific, recently discovered, microbialite carbonate reservoirs. The new phase in geophysical data acquisition and offshore drilling that started in 1999 bolstered the Brazilian offshore petroleum production to record levels. The new, massive, nonexclusive, speculative 2D and 3D data acquisition surveys conducted offshore the Brazilian coast far exceed the amount of all existing cumulative vintage data. Deepwater drilling programs probed the interpreted new prospects. As whole, the modern geophysics data libraries offshore Brazil brought in the technology era to seismic interpretation, reservoir characterization, and geosteering operations in deepwater development drilling. Still, regional interpretation mapping of the outer shelf, slope, deepwater and ultra-deepwater provinces of the Santos and Campos Basins indicates plenty of prospective future drilling in the salt locked minibasins of the ultra-deepwater provinces. Salt tectonics shapes the architecture of these basins; hence, postsalt deepwater turbidite plays were readily interpreted from seismic amplitudes of the modern data that also allow for resolution images of the synrift source rocks, salt architecture, migration paths through faulting and salt windows, reservoir characterization, and regional seal mapping. The new techniques of prestack depth migration have enabled uncovering the imaging structure of the synrift that led to characterization of the presalt carbonate reservoirs and discovery of giant accumulations. Future offshore exploration will continue aiming at postsalt deepwater and ultra-deepwater minibasins plus presalt plays under the massive salt walls, still an underexplored frontier.

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