Formation Characterization and Type Prediction Based on Geophysical Well Log Data in Horizontal Well: A Case Study of Triassic Chang 8 Formation in Shunning Region, Central Ordos Basin

Permeability is an important input parameter in Tight reservoir characterization and evaluation, precisely predicting formation permeability is indispensable. However, permeability prediction faces great challenge in tight sandstone reservoirs, empirical statistical methods, and nuclear magnetic resonance (NMR) based models lose their role due to complicated pore structure and the effect of methane gas (CH4) or hydrocarbon to NMR responses. In addition, fractures also play important role in improving tight reservoir permeability, whereas current logging responses cannot be used to characterize this improvement besides electrical image logging. In this study, to quantitatively characterize the improvement of fractures to filtration capacity in tight sandstone reservoir and accurately predict permeability, the Triassic Chang 63 Member of Jiyuan Region, Northwestern Ordos Basin is used as an example, a novel model of predicting permeability from electrical image logging is raised. In this model, the porosity frequency spectra are first extracted to characterize the pore structure of fractured tight sandstones. Afterwards, two parameters, which are defined as the logarithmic geometric mean value (φmv) and the golden section point variance (σg) of porosity frequency spectrum, are extracted to characterize the contribution of fractures to permeability. Comparing with the shape of porosity frequency spectrum, permeability φmv and σg, the quality of our target fractured tight sandstone reservoirs is quantified, and relationships among permeability, φmv and σg are established. High-quality reservoirs exhibit wide porosity frequency spectrum, high values of φmv and σg, and vice versa. Three parameters, which are formation total porosity, φmv and σg, are chosen to establish a novel fractured tight sandstone reservoir permeability prediction model. The involved input parameters in this model are calibrated by using the routine experiments of 35 core samples. Finally, we apply this model into field applications to consecutively calculate permeability in the intervals with which electrical image logging is acquired. Comparison of predicting permeability with core derived results illustrate that our raised model is usable in the Chang 63 Member of Jiyuan Region. The average relative errors between these two kinds of permeabilities is only 16.54% in 12 wells. This research gives a novel technique of calculating permeability in fractured tight reservoirs. It can avoid the effect of CH4 or hydrocarbon on conventional and NMR logging responses, and will play a great important role in unconventional reservoirs permeability prediction and formation characterization.

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Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: A case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

Xia,

Han,

Xie

et al. 2024

Preprint

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Water saturation estimation faced a great challenge in tight gas sandstone reservoirs because of the effect of pore structure and strong heterogeneity to rock resistivity. The classic Archie’s equation cannot be always well used. To quantify the effect of pore structure to rock resistivity in tight gas sandstones, taking the Triassic Xujiahe Formation of northwestern Sichuan Basin as an example, 35 core samples were recovered and applied for resistivity experiments in laboratory under the simulated formation temperature and pressure environment, and 18 of them were simultaneously applied for nuclear magnetic resonance (NMR) and high-pressure mercury injection (HPMI) experimental measurements. Relationships between rock pore structure and resistivity parameters were analyzed. The results clearly illustrated that cementation exponent (m) and saturation exponent (n) were heavily affected by pore structure. Rocks with superior pore structure contained relative higher cementation exponent and lower saturation exponent, and vice versa. Afterwards, we raised a parameter of pore size index, which was defined as the ration of macropore and micropore percentage contents, to reflect rock pore structure, and established a model to calculate optimal saturation exponent from NMR data. Meanwhile, various cementation exponent prediction model was also raised by combining with porosity and irreducible water saturation (Swirr). By combining with calculated cementation exponent and saturation exponent, we optimized the Archie’s equation to predict water saturation in our target tight gas sands. Field examples illustrated that the predicted cementation exponent and saturation exponent matched well with core-derived results. The absolute errors between predicted cementation exponent and saturation exponent with core-derived results were lower than 0.05 and 0.07, separately. By using the optimized Archie’s equation, water saturations were precisely predicted from well logging data in our target tight gas sandstone reservoirs.

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Formation Characterization and Type Prediction Based on Geophysical Well Log Data in Horizontal Well: A Case Study of Triassic Chang 8 Formation in Shunning Region, Central Ordos Basin

Cited by 3 publications

References 26 publications

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: a case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: a case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

A Novel Method of Predicting Fractured Tight Sandstone Reservoir Permeability from Electrical Image Logging

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: A case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

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