8results about How to "Reduce exploration risk" patented technology

This invention discloses a method, apparatus, equipment, and medium for oil and gas resource evaluation based on ensemble learning. The method includes acquiring reservoir sample data; preprocessing the reservoir sample data to obtain target reservoir sample data; constructing an oil and gas resource evaluation model based on the target reservoir sample data; and evaluating oil and gas resources based on the oil and gas resource evaluation model; wherein the oil and gas resource evaluation model is an oil and gas resource evaluation model based on ensemble learning. This technical solution, by constructing an oil and gas resource evaluation model using an ensemble learning method, can achieve refined prediction of oil and gas resource distribution, reduce exploration risks, improve resource utilization efficiency, and provide scientific decision support for oil and gas exploration and development.

The invention discloses a multi-element exploration and prediction method for hydrothermal cobalt ore. The method comprises the following steps: firstly, under the guidance of a regional metallogenic theory, delineating a cobalt ore prospecting prospecting area and a prospecting target area by integrating geological, geophysical prospecting and chemical prospecting data; secondly, performing large-scale geological mapping and remote sensing interpretation in the prospecting target area to identify structure and alteration marks, and delineating geophysical and geochemical exploration anomalies by using high-precision magnetic survey, induced polarization profiles and soil geochemical profiles; then, aiming at a geophysical and geochemical exploration abnormal part, a lithologic interface and a structural development part, utilizing a scribed line investigation sample to quickly position a mineralization favorable part, and utilizing groove exploration to carry out shallow earth surface control; then, the form, scale and resource potential of the deep ore body are verified through drilling engineering; and finally, establishing a prospecting prediction model by taking the target region with the outstanding prospecting effect as a model region, and guiding peripheral prediction. The method has the advantages of being convenient, environmentally friendly, remarkable in prospecting efficiency and the like, the purpose of rapidly recognizing the ore-bearing position of the cobalt ore is achieved, and a good cobalt ore prospecting effect is achieved in the East Kunlun inflator River region.

The present application belongs to the technical field of geophysical exploration, and relates to a method and system for improving seismic data resolution through frequency extrapolation, comprising: collecting a seismic signal, and representing the seismic signal by a reflection coefficient sequence and a seismic wavelet; fitting the reflection coefficient sequence to obtain a plurality of candidate fitting functions, selecting a function having the least influence on the reflection coefficient sequence from the fitting functions, and calculating an entropy norm of the reflection coefficient sequence according to the function having the least influence on the reflection coefficient sequence; converting the reflection coefficient sequence into a reflection coefficient in a frequency domain, performing frequency extrapolation on the reflection coefficient in the frequency domain through the function having the least influence on the reflection coefficient sequence, and solving an optimization problem through iteration; making the reflection coefficient obtained through the frequency extrapolation satisfy a coherence constraint condition, and outputting the frequency extrapolation reflection coefficient meeting the coherence constraint condition. The present application can effectively improve the seismic data resolution while maintaining the continuity of seismic events.

This invention belongs to the field of seismic data processing technology for petroleum exploration. It discloses a method for processing contiguous seismic data. The method involves coherent enhancement and Fourier transform of seismic traces in seismic data A and B, obtaining the phase and amplitude spectral factors of each trace in the frequency domain. After smoothing, the values ​​are summed and averaged to obtain the phase and amplitude factors in the frequency domain. Then, an inverse Fourier transform is performed to convert the data to the time domain, yielding phase and amplitude shaping operators. These operators are then convolved and sequentially applied to seismic data A to achieve contiguous data shaping from seismic data A to seismic data B. This invention is used for contiguous processing of seismic data and has advantages such as good stability, high accuracy, and strong applicability.

The application discloses a preferred method, device, electronic equipment and storage medium for constructing traps. The method comprises the following steps: determining a plurality of target structural traps of each target stratum corresponding to a target region based on a depth domain construction map of the target region; determining a first velocity corresponding to the target structural trap based on a blind well velocity field constructed by a well calibration average velocity and a root mean square velocity spectrum of a target well and a target stratum of the target structural trap, and determining a second velocity corresponding to the target structural trap based on an optimal velocity field and the target stratum of the target structural trap; predicting a burial depth error of the target structural trap based on the first velocity and the second velocity, determining a comparison result of the target structural trap based on the burial depth error of the target structural trap and a preset threshold, and determining a drilling sequence of the plurality of target structural traps based on the comparison result of each target structural trap. The embodiment solves the problem that the depth error of the structural trap affects the accuracy of the preferred structural trap, and avoids the influence of the velocity field construction error on exploration.

The application discloses a curtain opening system dissolution quantitative evaluation method under a high-temperature closed background, which comprises the following steps: carrying out source partition on a research area, determining mineral composition, interstitial type and pore type of different source areas, and determining compaction intensity sequence of different source areas; reconstructing a time-space sequence of diagenetic fluid activity, establishing a dynamic model of fluid-rock interaction and pore evolution; determining a mineral differential dissolution conversion mechanism; quantifying mineral differential dissolution under a curtain opening / closed system; and based on mineral composition component difference, fluid type and mineral dissolution effect difference, establishing a curtain opening system deep clastic rock reservoir dissolution quantitative evaluation method under a closed background by combining diagenetic mineral quantitative statistics and theoretical calculation. The application realizes quantitative-semi-quantitative prediction of dissolution effect, thereby delimiting a favorable dissolution development area, and effectively improves reservoir prediction precision, provides a scientific basis for drilling deployment, and reduces exploration risk.

The present application relates to a kind of stratum pinch-out line prediction methods based on geology-seismic combination, comprising the following steps: data collection;According to well logging electrical curve and core, select lithology-electricity marker layer, establish lithology-electricity relationship, determine development characteristics and interface identification mark;Establish regional well profile, clear sequence stratigraphic distribution law, construct stratum lateral variation geological model;Based on three-dimensional seismic work area, in combination with regional well profile, draw section stratum pinch-out trend line;Using stratum thickness method, refine pinch-out line position, clear stratum pinch-out line geological characteristics;Using single well stratum thickness and interwell horizontal distance, the included angle of pinch-out trend line at pinch-out point is obtained, average value of included angle;Through included angle extrapolation method, the position of pinch-out line is calculated and determined;Using seismic phase rotation processing method, the pinch-out point is identified and finely described;Based on the position of pinch-out line determined, in combination with the aforementioned analysis results, the distribution range of stratum pinch-out line is comprehensively predicted.

The invention relates to a shale organic matter enrichment main control factor quantitative characterization method and system based on machine learning, and belongs to the technical field of unconventional energy exploration evaluation. According to the method, a shale organic matter enrichment influence factor parameter system covering paleoclimate, paleo-productivity, oxidation-reduction conditions, terrestrial source input and deposition rate is constructed, the index collinearity problem is solved through principal component analysis dimension reduction processing, and a gradient boosting tree model is adopted to establish a nonlinear relation between multi-source geological parameters and organic matter enrichment degree. Systematic analysis is carried out by fusing four types of feature importance evaluation methods including statistical analysis, information theory, model structure and model interpretation, and a comprehensive influence value is converted into a standardized percentage to be output. According to the method, the accuracy and reliability problems of shale organic matter enrichment main control factor identification are effectively solved, conversion from qualitative description to quantitative characterization is realized, and a scientific and efficient quantitative technical support is provided for shale gas resource evaluation and exploration deployment.