Rock type prediction and 3D modeling of clastic paleokarst fillings in deeply-buried carbonates using the Democratic Neural Networks Association technique

On the Pore Geometry and Structure Rock Typing

“…Samples in each class seem indistinguishable due to similar geological depositions and diagenetic alterations . Many methods have addressed rock typing, for example: Based on mechanical properties, mineralogy, and organic geochemistry The use of permeability, porosity, and irreducible water saturation data either empirically ,− or with a hydraulic flow unit (HFU) approach; ,, Involvement of capillary pressure data and J -function − and combined with radius; Consideration of thin section descriptions and interpretations such as rock fabrics, depositional facies, and rock textures; , Geostatistics and machine learning implementation such as clustering, , ANN, self-organizing map, , and fuzzy logic; Grouping based on the dimensionless form of absolute permeability, relative permeability, porosity, and phase viscosity, the so-called true effective mobility TEM function; , The use of resistivity data and porosity to yield in electrical flow unit; Further development of analytical models, such as the pore geometry and structure (PGS) method. − …”

“…Geostatistics and machine learning implementation such as clustering, , ANN, self-organizing map, , and fuzzy logic;…”

“…• Based on mechanical properties, mineralogy, and organic geochemistry 7 • The use of permeability, porosity, and irreducible water saturation data either empirically 5,8−10 or with a hydraulic flow unit (HFU) approach; 1,3,11 • Involvement of capillary pressure data and J-function 12−14 and combined with radius; 5 • Consideration of thin section descriptions and interpretations such as rock fabrics, 15 depositional facies, 16 and rock textures; 17,18 • Geostatistics and machine learning implementation such as clustering, 19,20 ANN, 21 self-organizing map, 22,23 and fuzzy logic; 24 • Grouping based on the dimensionless form of absolute permeability, relative permeability, porosity, and phase viscosity, the so-called true effective mobility TEM function; 25,26 • The use of resistivity data and porosity to yield in electrical flow unit; 27 • Further development of analytical models, such as the pore geometry and structure (PGS) method. 28−31 The PGS method is built on the basis of the Kozeny−Carman and capillary bundled model equations, ending up with a plot between y k/ and x � k/ϕ 3 within a power function y = ax b28, 29 such that The inspiration came from the facts that many physical phenomena in nature are in a power law scaling relationship.…”