Comparative Evaluation of Pore Structure Heterogeneity in Low-Permeability Tight Sandstones Using Different Fractal Models Based on NMR Technology: A Case Study of Benxi Formation in the Central Ordos Basin

Abstract

Based on the NMR T 2 spectra of all of the samples, the applicability of the single fractal model and the multifractal model for the quantitative investigation of pore diameter distribution heterogeneity is analyzed. Then, the relationships between pore structures, physical properties, and fractal dimensions calculated by each model are discussed. The following results have been achieved. (1) Model 1 can be used to study the heterogeneity of different fluid states (including saturation and bound water) or partial pore size distribution, and the calculated fractal dimension has the best correlation with permeability. This model is mainly suitable for type I samples with macropores developed. (2) Models 2, 3, and 4 can quantitatively analyze the heterogeneity of the overall pore diameter distribution. These calculated fractal dimensions have a good linear relationship with porosity, T 2cutoff, T 2gm, and other physical parameters, which are mainly suitable for type II, III, and IV samples with micropores developed. (3) There is a negative correlation between multifractal dimensions calculated by model 4 and single fractal parameters calculated by models 2 and 3. Micropores and macropores are the key pore sizes that affect the variation of single fractal parameters, while mesopores are the key size affecting the variation of multifractal parameters. (4) The selection of a reasonable T 2 spectrum range has become a key to determine the calculation accuracy of models 2 and 3. Above all, models 1 and 4 should be given priority in characterizing pore distribution heterogeneity of tight sandstone gas reservoirs.

Classifications of the Reservoir Space of Tight Sandstone Based on Pore Structure, Connectivity, and Fractal Character: A Case Study from the Chang 7 Member of the Triassic Yanchang Formation in the Ordos Basin, China

“…Many scholars have successfully applied fractal theory to investigate the pore structure of coal and sandstone. 29 , 30 The increase in the fractal dimension indicates rough surfaces and complex structure of the pore space, and the decreasing in the fractal dimension indicates a regular shape and a smooth pore surface. 19 , 31 , 32 The fractal dimension is an important symbol to characterize the pore structure.…”

Multifractal Analysis and Neural Network Prediction of Pore Structures in Coal Reservoirs Based on NMR T2 Spectra

“…Currently, porosity, pore size distribution, and fluid saturation of coal samples are calculated by combining T 2 spectra in saturated and centrifuged states. The T 2 distribution is a highly disordered system with self-similar characteristics and can be further analyzed based on fractal theory. , The fractal theory includes monofractal and multifractal. Monofractal is limited to the overall and average description of the pore size distribution and cannot reflect the complex fractal characteristics of different regions or scales.…”

Nanopore Size Distribution Heterogeneity of Organic-Rich Shale Reservoirs Using Multifractal Analysis and Its Influence on Porosity–Permeability Variation

“…However, the above model can only describe shale nanopore size distribution heterogeneity (SNDH) simply by a single fractal dimension. For shale reservoirs with strong heterogeneity, the pore size distribution (PSD) curve usually fluctuates or jumps randomly and different pore size intervals may have different types of self-similarity, and so it is difficult to fully characterize pore homogeneity with a single fractal dimension. , To overcome this, a multifractal approach can be adopted, in which a fractal body is divided into small regions with different singularities. The advantage of studying the fractal characteristics of these different regions is that it enables the detailed structure to be understood hierarchically and allows multiple characteristics of the pore size distribution of reservoirs to be analyzed based on HPMI, LPN 2 GA, and low field nuclear magnetic resonance (LF-NMR) test data.…”