6results about How to "Improve exploration efficiency" patented technology

The application discloses a method and system for predicting deep hydrocarbon source rock organic matter enrichment law based on glowworm algorithm optimized GBDT, and belongs to the field of hydrocarbon source rock TOC prediction. Specifically, the method comprises the following steps: obtaining logging curve data; preprocessing the obtained logging curve data; based on the preprocessed data, establishing a machine learning model (the core lies in the hyperparameter optimization of the model, and the glowworm algorithm is particularly used in the optimization process); and using the established TOC prediction model to predict the total organic carbon content. The application combines machine learning and intelligent optimization algorithm and predicts the organic matter enrichment law of deep hydrocarbon source rock, which can greatly improve the prediction accuracy and precision, and reduce the exploration cost and risk.

The application provides a relative velocity analysis well-free constraint relative wave impedance inversion method, which comprises the following steps: step 1, velocity analysis is carried out by using seismic data to establish the time-depth relationship of a study area; step 2, seismic facies analysis is carried out on the seismic data to determine the geological model of the study area; step 3, velocity correlation analysis is carried out to determine the velocity migration amount; step 4, the velocity curve of a seismic trace is extracted; step 5, relative velocity normalization analysis of different lithologies at the same depth point is carried out; step 6, relative velocity wave impedance inversion processing is carried out; and step 7, lithology and reservoir identification, tracking and description are carried out. The relative velocity analysis well-free constraint relative wave impedance inversion method breaks through the limitation of conventional inversion which can only be used for single target layer and time domain wave impedance inversion, eliminates the influence of different velocities in time domain and depth domain of multiple target layers, and provides relative wave impedance inversion data for lithology or reservoir prediction under complex conditions in a well-free exploration area.

This invention provides a method for predicting deep solid potash deposits using brine hydrogeochemical simulation. The core of this method lies in using brine to locate potash. By simultaneously collecting surface saline spring water and deep borehole brine from the same target area, the method calculates and compares the brine characteristic coefficients of both. Based on this invention, a quantitative relationship of brine coefficient thresholds is proposed to determine the brine's formation, evaporation rate, and the influence of atmospheric precipitation. Brine samples indicating favorable deep potash-forming environments are screened. Then, a hydrogeochemical model is constructed and corrected, and the simulated evaporation mineral precipitation sequence is performed on the screened samples. The saturation indices of target minerals such as halite and carnallite are calculated. The core criterion is that the SI value of halite approaches -0.5 to +0.5, combined with the fact that halite is unsaturated and carnallite is nearly saturated. The exploration target area is delineated using a comprehensive multi-indicator approach. This invention aims to significantly improve the prediction accuracy and exploration efficiency of deep solid potash deposits under complex geological conditions.

This invention provides a method and apparatus for predicting in-situ stress and selecting fracturing zones in volcanic rock reservoirs, belonging to the fields of geological engineering and petroleum exploration technology. The method for predicting in-situ stress in volcanic rock reservoirs includes: acquiring pre-stack seismic data and well logging data of the area to be tested; performing joint inversion using the pre-stack seismic data and well logging data; obtaining a first rock mechanical parameter based on the inversion results; calculating a second rock mechanical parameter based on the first rock mechanical parameter; performing azimuth anisotropy inversion using the pre-stack seismic data to obtain a third rock mechanical parameter; and calculating the in-situ stress of the area to be tested based on the first, second, and third rock mechanical parameters. This invention improves the accuracy of in-situ stress prediction in volcanic rock reservoirs by comprehensively considering various formation characteristics, which helps optimize the selection of fracturing zones and improve the efficiency and economic benefits of petroleum exploration and development.

This invention relates to the field of geological exploration technology, specifically disclosing a coal mine hydrogeological exploration device and method. The device includes a drill rod having a first rod section and a second rod section, the diameter of the first rod section being larger than the diameter of the second rod section; an exploration component including a first ring and a second ring sleeved on the second rod section, the outer diameter of the first ring and the second ring being the same as the diameter of the first rod section, and the first ring and the second ring being connected by a folding curtain, the folding curtain having through holes; by setting the exploration component on the drill rod, when drilling reaches the exploration position, the first ring and the second ring are controlled to move away from each other along the second rod section, causing the folding curtain to unfold. The folding curtain contacts the inner wall of the borehole, providing a supporting effect and forming an exploration space within the borehole, avoiding the problem of borehole wall collapse leading to the inability to conduct normal exploration.

A method and apparatus for evaluating reservoir oil-bearing potential based on gas logging data, the method comprising: acquiring raw total hydrocarbon data and gas logging influencing factor data of a target formation in a study area; determining correction coefficients for each gas logging influencing factor, and obtaining corrected total hydrocarbon data based on the correction coefficients and raw total hydrocarbon data; calculating a similarity factor and a saturation factor using the corrected total hydrocarbon data; and determining the oil-bearing potential of the target formation based on the similarity factor and the saturation factor, and using a pre-established gas logging data interpretation chart in the study area.