The Permian igneous rocks in the Sichuan Basin represent a major breakthrough, opening up a new prospect for oil and gas exploration, and igneous reservoirs have become a new field of oil and gas exploration. Gravity-magnetic-electric exploration is an effective means of identifying igneous rocks and helps in reducing the multiplicity of the prediction results. However, the lithology of igneous rocks is quite different, and the exploration theory and evaluation techniques need urgently to be improved. In order to deeply study the response characteristics of the gravity-magnetic-electric and physical properties of the Permian igneous rocks in the Sichuan Basin and their relationships with the reservoir parameters, physical property testing was carried out on outcrop samples of the Permian igneous rocks in southwestern Sichuan. The comprehensive physical properties of the samples with different lithologies, including basalt, tuff, and volcanic breccia, were analyzed and studied. Based on the geological characteristics of the igneous rocks, such as the mineral composition, microstructure, and reservoir properties, a multi-parameter intersection relationship model for the resistivity, polarizability, density, magnetic susceptibility, and their relationships with the reservoir parameters was established, and effective parameters favorable for igneous rock identification and reservoir evaluation were identified. The results of this study provide a physical basis and technical support for non-seismic exploration of igneous oil and gas reservoirs in the Sichuan Basin.

The land controlled-source electromagnetic (CSEM) method dynamically monitors reservoir fluid by contrasting electrical conductivity between hydraulic fracturing fluids and surrounding rock formations. In hydraulic fracturing monitoring, the underground steel casings represent significant high-conductivity objects that require accurate and rapid numerical modeling for understanding the CSEM responses and optimizing the survey configurations. To efficiently simulate the steel well casings, we made use of the modified finite volume method (FVM) with the concept of edge conductivity equivalence that avoids the computational cost of grid refinement down to millimeters or centimeters for the casing. The new algorithm is satisfactorily validated by a numerical comparison against a trusted program Dipole1D and a commercial program COMSOL. Then the algorithm is used to investigate the characteristic CSEM responses of injected fracturing fluid due to a galvanic electromagnetic (EM) source grounded near the head of steel-cased well, an unconventional configuration that can maximize the data anomaly by channeling more excitation current to the deep reservoir. In particularly, we simulated two fracturing scenarios with different fluid migration directions: one with a high-resistivity cap layer as the background and the other with a realistic heavy oil fracturing site from Karamay in Xinjiang, China. Our simulation shows that the configuration of near-casing excitation significantly enhances the electric-field anomalies of the fluid injection, which is the most prominent as the galvanic effect at low frequencies. These phenomena highlight the crucial role of steel casing in the CSEM method for hydraulic fracturing monitoring.

We describe a novel integrated algorithm for real-time enhancement of video acquired under challenging lighting conditions. Such conditions include low lighting, haze, and high dynamic range situations. The algorithm automatically detects the dominate source of impairment, then depending on whether it is low lighting, haze or others, a corresponding pre-processing is applied to the input video, followed by the core enhancement algorithm. Temporal and spatial redundancies in the video input are utilized to facilitate real-time processing and to improve temporal and spatial consistency of the output. The proposed algorithm can be used as an independent module, or be integrated in either a video encoder or a video decoder for further optimizations.