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The Triassic Chang 8 Formation in Pengyang Region, Southwestern Ordos Basin, belonged to typical near-source hydrocarbon-bearing reservoirs; the hydrocarbon accumulation mode did not meet the classical law. This led to low resistivity contrast between hydrocarbon-bearing reservoirs and water saturated layers, and the common methods of identifying hydrocarbon-bearing potential reservoirs based on geophysical well logging data lose their role. In this study, based on the analysis of petrophysical experiments and geological structure, we concluded that the main reason that led to low resistivity contrast in the Chang 8 Formation was high irreducible water saturation (Swirr), and the key factors that controlled pore fluid distribution contained the effective thickness of source rock, the straight-line distance between effective source rock and the top depth of Chang 8 Member, and the reservoir quality. Hydrocarbon-bearing formations always contained good quality, short straight-line distance between Chang 8 Member and effective source rock and corresponded to thicker source rock, and vice versa. We defined three parameters of RQI, H1 and H2 to express the quality of Chang 8 Member, the effective thickness of source rock of Chang 7 Member and the straight-line distance between Chang 8 and Chang 7 Members, and a combined factor of (Rt × RQI) × H2/H1 was raised to identify near-source hydrocarbon-bearing potential reservoirs. Meanwhile, the crossplot of water saturation (Sw) and free water saturation (Swf) was also proposed to distinguish low resistivity contrast near-source hydrocarbon-bearing potential reservoirs and water saturated layers. Comparing with common methods, the identification accuracy of near-source hydrocarbon-bearing potential reservoirs in the Chang 8 Formation increased from 68.75% to 93.75%. [ABSTRACT FROM AUTHOR] more...

Comparing with conventional formations, the resistivity difference between the oil-bearing reservoir and water-saturated layer is little in the Triassic Chang 3 Member of the Yanchang Formation in Pengyang Region, southwestern Ordos Basin, China. This makes the oil-bearing potential reservoirs' identification face a great challenge. To understand the genesis that makes the low-resistivity contrast in oil-bearing formations, several core samples are chosen to apply for routine physical property and X-ray diffraction analysis, nuclear magnetic resonance (NMR), and mercury injection capillary pressure (MICP) experimental measurements. Meanwhile, the formation water is also extracted from 19 wells to measure the total salinity and analyze the chemical components. The results illustrate that the Chang 3 Formation contains good pore structure and relative high porosity and permeability (the average porosity is 13.80%, and the average permeability is 6.81 mD). The effect of clay mineral to formation resistivity can be ignored. The main factors that cause low-resistivity contrast in oil-bearing layers are high formation water salinity and formation porosity. Combining the spontaneous potential (SP) with formation deep induction resistivity (RT), a parameter, named as the corrected resistivity index (CRI), is constructed, and the crossplots of reservoir porosity and CRI and flow zone index (FZI) versus CRI are raised to identify low-resistivity contrast oil-bearing layers in the northeastern and southwestern areas, separately. In addition, after normalizing porosity and CRI, the correlation coefficient between these two parameters is also calculated and used to indicate low-resistivity contrast oil-bearing potential layers. After these methods are extended to field applications, the oil-bearing potential formations in the Chang 3 Member are consecutively identified. The identification results match well with the drill stem test (DST) data, verifying the reliability of the proposed methods. [ABSTRACT FROM AUTHOR] more...

Recent field applications of nuclear magnetic resonance (NMR) logging in wells that drilled with salt mud illustrate a lack of precise formation porosity and pore structure characterization because of the effect of mud filtrate concentration. In this study, 33 core samples were chosen for laboratory NMR experiments to demonstrate the effect of saturated brine's concentration on NMR T2 responses. These core samples were separately recovered from tight, low-permeability sandstones and conventional reservoirs in two adjacent regions A and B. Each core sample was saturated with seven concentrations (0.0, 5.0, 20.0, 30.0, 50.0, 80.0, and 100.0 g/l) of brine. The experimental results illustrate that the NMR porosity and the shape of T2 distribution for core samples with porosity higher than 20.0% change significantly when the concentrations of saturated brine are higher than 80.0 g/l. An additional peak appears with the T2 relaxation time ranging from 11.0 to 40.0 ms, limiting the applicability of NMR logging in high-porosity sandstone reservoirs drilled with high-salinity mud. Based on the theoretical simulation, the relationship between the salinity and hydrogen index (HI) (defined as the ratio of the number of hydrogen atoms per unit volume to that of pure water at surface conditions) is established, and a method of correcting NMR porosity is proposed. Meanwhile, a model to correct the shape of the NMR T2 spectrum is also established. Based on the proposed method and model, the effect of saturated brine on NMR porosity and the shape of T2 spectrum in high-porosity reservoirs are eliminated. The accurate formation porosity, permeability, and NMR T2 spectra are acquired. Field applications of our target region B validate the reliability of the established method and model. [ABSTRACT FROM AUTHOR] more...

Tight sandstone reservoir evaluation and characterization faced great challenge by using conventional well logging data due to the complicated pore structure. To improve tight sandstone reservoir identification, the pore structure should be first characterized. In this study, using the tight Chang 8 Formation of Pengyang Region, west Ordos Basin as an example, 20 core samples were drilled for laboratory nuclear magnetic resonance (NMR) and mercury injection capillary pressure (MICP) experiments. A model, which was used to construct capillary pressure (Pc) curves from NMR data, was proposed, and the corresponding models were established based on classified power function (CPF) method to classify formations into three types. Based on these relationships, the NMR T2 distributions were transformed as pseudo Pc curves and pore throat radius distributions. After these relationships were extended into field applications, consecutive pseudo Pc curves were acquired, and the pore structure evaluation parameters and permeability were also predicted. Comparisons of predicted parameters with core-derived results illustrated the reliability of our proposed model and method. [ABSTRACT FROM AUTHOR] more...