172 results about "Seismic facies" patented technology

The invention belongs to the technical field of oil gas and coal-bed gas seismic exploration and development, and in particular relates to a reservoir sedimentary evolution analysis method in the exploration and development process. The method is used for providing reliable basic data for optimizing favorable target bed series and zone for oil gas and coal-bed gas exploration and development. In the method, sedimentary characteristics of reservoirs are analyzed by a three-dimensional seismic attribute data body, and high-resolution sequence stratigraphic principle and method, a seismic attribute analysis method and a pattern recognition method are applied; and a K-mean clustering algorithm is adopted, and the analysis process of sedimentary characteristics and sedimentary evolution of a sedimentary formation unit is performed under the control of a sedimentary isochronous interface. The method is used for assisting in reservoir sedimentary evolution research work in the exploration and development process of oil gas including unconventional oil gas, guiding the description of sedimentary characteristics of fine reservoirs of lithologic and stratigraphic trapped oil gas reservoirs, and providing the reliable basic data for optimizing the favorable target bed series and zone for the oil gas and coal-bed gas exploration and development.

The embodiment of the invention provides a seismic waveform analysis and reservoir prediction method and device; the method comprises the following steps that: a target reservoir is selected; the size of a window when in seismic waveform classification is selected; a plurality of model traces are created according to the number of categories of seismic facies; different waveforms are classified according to a self-organizing neural network; seismic facies classification parameters are processed to generate a seismic facies classification diagram; sedimentary facies identification signs are established to classify the sedimentary facies of a single well, the sedimentary facies of the single well are compared to generate the sedimentary facies of a well tie, so that the sedimentary facies between the wells are determined; the seismic facies at a well point are converted into sedimentary facies by integrating the sedimentary facies of the single well and the seismic facies; external pushing is carried out towards an area which is not drilled according to the seismic waveform type of the calibrated well point; geological interpretation is carried out to the whole seismic facies diagram by integrating the sedimentary facies of the well tie, and a sedimentary facies diagram is formed from point to surface; and reservoir prediction is carried out according to the sedimentary facies diagram. According to the method, research and reservoir prediction for a sedimentary facies belt can be facilitated, so that the working efficiency of exploration is improved.

An method of constructing a geological model of a subsoil formation constrained by seismic data having application to petroleum reservoir development is disclosed. Logs relative to geological properties are acquired and a seismic facies cube is constructed. Logs relative to geological properties and logs relative to seismic facies are then simulated. Then distribution of proportions is estimated at any point on the subsoil by means of the acquired logs in the well and of the simulated logs. A seismic constraint is then defined by constructing a lithologic facies average proportion cube from these estimated proportion distributions. Finally, a geological model wherein the geological properties are constrained by this lithologic facies average proportion cube is constructed.

The invention provides an igneous rock oil and gas exploration method and an igneous rock oil and gas exploration device. The method comprises the following steps of generating crater position and igneous rock lithofacies information according to the position of an igneous rock reservoir and characteristic information; generating geophysical reflection characteristic data according to seismic facies analysis, and determining a distribution range of advantageous lithofacies; calculating a stratigraphic strike-slip distance of a deep igneous rock mechanism according to a matching relation of target stratum lithofacies of a volcanic edifice on two sides of a fracture and a corresponding relation of igneous rocks of a middle-shallow layer on the two sides of the fracture; analyzing logging response data of the igneous rocks, and generating advantageous lithology distribution information and thickness data of the deep igneous rock mechanism through natural gamma seismic inversion; acquiring a development part of the fracture of the igneous rock reservoir by using means such as deep and shallow resistivity difference inversion; and generating igneous rock oil and gas reservoir information in the development part through cluster analysis of seismic attributes and two-phase media-based oil and gas detection. By the invention, the accuracy of exploring and predicting the igneous rock oil and gas reservoir and the drilling success rate can be improved.

The invention provides a seismic inversion system and a seismic inversion method controlled by geologic facies. The seismic inversion system and the seismic inversion method controlled by the geologic facies comprises a geologic facies establishing module which establishes the geologic facies on a destination layer of a well point position, a seismic facies establishing module which establishes a seismic facies on a plane of the destination layer, a geologic facies constraint establishing module which establishes constraint to the geologic facies, a stochastic inversion module which chooses the number of constraint wells and conducts stochastic inversion controlled by the geologic facies, an analysis module which analyzes inversion data volume and further subdivides the geologic facies, and an output module which iterates repeatedly so as to obtain and output the three-dimensional inversion data volume. The seismic inversion system and the seismic inversion method controlled by the geologic facies solves the problem that due to the fact that geological sedimentary background and regularity in an inversion work area are not considered by the existing inversion method, and inversion results are often horizontally different from geological sedimentary regularity cognition. The seismic inversion system and the seismic inversion method controlled by the geologic facies has the advantages of being capable of accurately depicting oil deposit on the basis of control of the geologic facies.

The invention provides a method for analyzing waveform similarity body curvature of seismic data, which is a technology for processing and explaining oil seismic exploration data and realizes a method of accurately engraving sedimentary facies zone distribution by using the seismic data. The method for analyzing the waveform similarity body curvature of the seismic data comprises the following steps of: first, carrying out horizon flattening on original three-dimensional seismic data bodies by using a horizon flattening technology or a Wheeler automatic transform technology according to the described horizon so as to eliminate influences of a structure on lithofacies distribution; and then selecting a proper calculated aperture; figuring out a curvature based on a waveform similarity body by using a trend surface analysis method on the basis of extracting a waveform similarity information data so as to obtain multiple waveform similarity body curvature attribute data bodies. By using the method provided by the invention, strata bend, strata sedimentary facies or transverse variation of lithology caused by structure deformation can be effectively identified so as to provide a basis for describing distributional characteristics of reservoir lithology, indicating edges of the sedimentary facies zone and dividing a seismic facies zone.

The invention discloses a representation method for diagenetic seismic facies of a sandstone reservoir. According to the representation method for the diagenetic seismic facies of the sandstone reservoir, quantitative indexes of typical rock electric parameters for reflecting the diagenetic characteristic of the sandstone reservoir and the environment are utilized to accurately evaluate the diagenetic facies longitudinal phase sequence of the sandstone reservoir of a non-core hole and the plane distribution and the rule of the diagenetic facies of the target stratum reservoir, more effective technical information is provided for sandstone oil and gas exploration and development, favorable blocks of the sandstone oil and gas exploration and development are optimized, the forecasting accuracy of the favorable blocks is improved, the success rate of exploration and development is improved, and the cost of exploration and development is lowered.

The invention provides a method for classifying supervised waveforms in a three-dimensional seismic signal. The method mainly includes the steps of data preprocessing, feature selection and classified identification. The method has the advantages that the method is based on three-dimensional seismic signal resources and well logging data information, extracted attributive characters are optimized through a genetic algorithm, analyzed three-dimensional seismic target interval data undergoes waveform classification by means of an SVM classification algorithm, different seismic facies are recognized, and therefore reliable supports are provided for follow-up seismic resource explanation, and reliability of lithology prediction, sand body prediction, fractured reservoir prediction, elusive reservoir prediction and the like is improved. Compared with an SVM design classifier, the method carries out feature selection through addition of the genetic algorithm, design complexity of the SVM classifier is reduced, and therefore waveform classification processing efficiency is improved.

The present invention relates to a seismic facies control-based sedimentary microfacies recognition method. The method includes the following steps that: 1) logging information is normalized; 2) fine horizon calibration is performed; 3) a model framework is determined; 4) a low frequency model is established; 5) a seismic data impedance value and a formation reflection coefficient are obtained, if synthetic trace data are in optimal matching with an actual seismic data trace, and drilling impedance is in optimal matching with seismic data impedance, and the method shifts to step 6), otherwise, the method shifts to the step 3); 6) well seismic constraint inversion is performed, a wave impedance inversion data body is obtained; 7) the top and bottom of a reservoir are traced and explained, with the top reflection layer and bottom reflection layer of the reservoir adopted as control surfaces, interlayer attributes are extracted from the inversion data body; and 8) seismic attributes are utilized to constrain the boundaries of sedimentary microfacies, and the spread of the sedimentary microfacies is described. According to the method, the logging information is adopted to constrain seismic inversion, and therefore, the resolution of an inversion result can be improved, the sedimentary microfacies of a target interval can be well depicted, the planar distribution of a thin sand layer can be predicted, and a basis can be provided for well location deployment.

In a computer system and a computer-implemented method for determining a damage index indicative of damage caused by an earthquake to a portfolio of objects associated with a geographical area, local portfolio replacement value indices are stored assigned to object or grid coordinates of the geographical area. For each coordinate having a local portfolio replacement value index assigned to it, a local damage index is calculated from location, depth, and magnitude data related to the earthquake and from the local portfolio replacement value index, using local vulnerability and attenuation parameters. The damage index is calculated by aggregating the local damage indices for the grid coordinates. For any size of the geographical area and for any resolution of the grid, a damage index reflecting the geographical distribution of the portfolio objects can be determined, without need for a network of seismological measurement stations distributed in the geographical area.

The invention discloses a classification model channel extracting seismic facies clustering analysis method, which comprises the steps of acquiring an initial classification model channel through neural network and particle swarm clustering calculation based on seismic waveform data; acquiring a new classification model channel through correlation analysis based on the initial classification model channel, carrying out clustering analysis on original data by using the new classification model channel, and acquiring a seismic facies classification figure; and predicting distribution of oil gas underground based on the seismic facies classification figure. According to the invention, the classification model channel is optimized through a two-step method, thereby effectively ensuring the stability of a classification result and effective discrimination of classes of neurons, finally realizing objective analysis for the seismic facies, and enabling a large amount of information in the seismic data to be interpreted accurately.

The invention discloses a seismic facies pickup method. According to the method, a multi-task deep convolutional neural network model is constructed; a weighted classification loss function is defined; a classification and regression combined loss function is designed; training, verifying and testing are carried out on the model by utilizing an acquired large-scale three-directional station waveform data set of a station network in a certain region, and the seismic phase is detected, recognized and accurately picked up when arriving at time, then a transfer learning and data enhancement methodis adopted, the model is applied to training, verification and testing of a small-scale data set of a transformer network in a target area, and seismic phase picking-up in the target area is achieved. According to the method, the multi-task convolutional neural network is utilized to simultaneously realize detection identification and time-of-arrival estimation of the seismic facies, accurate seismic facies pickup of a target area with only a small data set is realized by utilizing transfer learning, and the problem of seismic facies pickup is solved.

The invention provides a foreland basin deep buried and compressed type complex gypsum-salt rock identification and distribution prediction method. The method comprises the following steps that: according to lithological vertical change in outcrop data, drilling data and logging data, a lithological sequence caused by sedimentary environment change is reserved, and a gypsum-salt rock deformation and overlying sequence caused by tectonic compression and fault repetition is eliminated, and an original lithologic sequence is established, and an ancient landform model of a research area is recovered through the original lithologic sequence, and a current tectonic model is recovered; and three-dimensional gravity, magnetic, electric and seismic joint inversion is carried out, and lithological and lithofacies interpretation of gypsum-salt rock at the surrounding region of a borehole is carried out through electrical methods, seismic facies and density anomaly and by means of the original lithologic sequence and the current tectonic model, and therefore, a lithological sequence plane distribution rule can be determined. According to the method provided by the invention, based on foreland basin gypsum-salt rock deformation characteristics which are obtained through geologic modeling, and geophysical methods such as three-dimensional gravity, magnetic, electric and seismic methods are adopted to perform joint inversion, and therefore, the distribution characteristics of post-deformation gypsum-salt rock can be accurately determined.

The invention relates to a seismic sedimentology reservoir prediction system which comprises a data acquisition device (1), a data quality analysis device (2), a seismic geomorphology analysis device (3), a seismic petrology analysis device (4), a reservoir prediction device (5) and a reservoir output device (6), wherein the data acquisition device (1) is connected with the data quality analysis device (2); the data quality analysis device (2) is respectively connected with the seismic geomorphology analysis device (3) and the seismic petrology analysis device (4); the seismic geomorphology analysis device (3) and the seismic petrology analysis device (4) are simultaneously connected with the reservoir prediction device (5); and the reservoir prediction device (5) is connected with the reservoir output device (6). The seismic sedimentology reservoir prediction system effectively solves the problems of diachronous complicated sedimentary stratum and isochronous stratal slicing in manners of driving data and automatically tracking seismic lineups. The seismic sedimentology reservoir prediction system has the beneficial effects that based on seismic geomorphology plane identification, a seismic facies is calibrated through the seismic petrology research; and through chronostratigraphic cyclic domain slicing, the palaeosedimentary environment is recovered, and the reservoir evolution is developed in two domains to describe the distribution of a favorable reservoir. The system has good application effect and promotion prospect.

The invention discloses a calculating method and system of a well-to-seismic integration average speed field. The method comprises the steps of: utilizing a well logging facies type of a target layer and a seismic facies type of the target layer to dividing a sedimentary facies of the target layer, encoding the sedimentary facies, and obtaining a sedimentary facies code; utilizing an earthquake to superpose speed fields, and by utilizing a Dix formula to calculate an earthquake average speed; utilizing well logging data to calculate a well logging average speed at each well drilling position of the target layer; and using the sedimentary facies code as a bound term, using the earthquake average speed as a secondary variable, using the well logging average speed as a main variable, utilizing a Co-Kriging estimating algorithm to carry out Co-Kriging interpolation, and obtaining a well-to-seismic integration average speed field. According to the invention, the high-precision well-to-seismic integration average speed field calculating method under the sedimentary facies constraint is utilized, and the consistence between a speed field transverse change trend and practical geological characteristics is ensured, so that the time-depth conversion precision of a structural map is improved.

The invention discloses a fluvial facies reservoir step-by-step seismic facies prediction method based on geological information constraint. The method includes following steps: assessing geological data; establishing an analysis column chart, and comprehensively analyzing the column chart and a work area river channel sand body to obtain a superposition relation; abstracting a seismic response model; constructing a seismic sensitive attribute set; recognizing a seismic mode by employing a probabilistic neural network; performing related preprocessing operation on the seismic attribute; and performing seismic facies prediction to obtain a seismic facies map. The method is advantageous in that geological information is converted to monitoring information of the seismic scale and added to mode recognition of the seismic facies so that prediction results are more accurate, and clearer geological significance is achieved; the seismic facies prediction is performed by employing the probabilistic neural network so that clear indication significance is achieved for final seismic facies prediction results; the training time is greatly saved by employing the network training method; and the reservoir seismic facies in the range of the seismic scale can be fully predicted through the step-by-step prediction method without setting a classification number in advance.

A system for predicting hydrocarbon production from a subterranean region of interest using reflection seismic data. The system sets a drainage area around reference traces and defines drainage pathways extending outwardly from the reference trace towards the perimeter of the drainage area. A mathematical combination of the trace-to-trace coherence factors and reservoir quality attributes along each drainage pathway is calculated for each reference trace, thereby providing an indication of both initial and sustained hydrocarbon production from that location.

The invention discloses a method for fine calibration of the position of a sand shale thin interbed. The method comprises the steps of 1, determining log layering and single well facies features of a marker bed and the sand shale thin interbed under the guiding of lithofacies and log facies modes; 2, loading seismic and logging data; 3, judging section polarity; 4, identifying and analyzing the seismic section features of the marker bed and the seismic facies features of the sand shale thin interbed; 5, determining the basic frequency of well side seismic channel seismic data by means of statistic wavelets, and selecting a Ricker wavelet of the basic frequency for primary calibration of the marker bed under the guiding of the seismic facies mode; 6, selecting a definite wavelet for secondary calibration; 7, adopting a time-varying wavelet for research of corresponding relation between a whole well and a multi-target stratum; 8, verifying a calibration result according to the relation between amplitude and reflection coefficient sequence envelope. The method has great basic significance for exploration, development, research and application of sand shale thin interbed oil deposit.

The invention discloses a waveform classification method based on dynamic time warping and partitioning algorithm. A seismic data sample set is determined; according to types of seismic facies in the seismic data sample set, a classification number k of the seismic data sample set is determined; k samples are selected in the seismic data sample set to serve as an original clustering center; on the basis of a DTW distance, sample data which are not selected as the original clustering center are allocated to a cluster in which a corresponding centroid is located; the centroid of the cluster is iteratively updated; whether an iteration number upper limit is reached is judged, if yes, the operation is completed, and k clusters allocated finally are obtained; or, the fourth step is executed continuously according to the updated centroid of the cluster obtained in the fifth step, and re-allocation is carried out. The seismic data are aligned by adopting dynamic time warping, influences of horizon interpretation errors are reduced, and similarities of two channels of seismic data are measured more accurately; the centroid of the cluster is used for serving as the center of the cluster, and compared with the center of the cluster defined by the traditional partitioning algorithm, more accuracy is achieved, and features of the cluster can be better represented.

The invention discloses a seismic facies analysis method based on prestack seismic data. The method includes the first step of inputting the prestack seismic data; the second step of splitting the input prestack seismic data to obtain N poststack-like data volumes, wherein N is the number of channels of seismic signals; the third step of carrying out SOM clustering analysis on the N poststack-like data volumes; the fourth step of conducting similarity analysis on the prestack data by means of clustering analysis results, generating a similarity matrix through statistics and constructing an undirected graph; the fifth step of carrying out clustering processing on the undirected graph by means of breadth-first traversal. The invention provides a prestack attribute clustering method based on an undirected connected graph. On the basis of prestack signals, SOM clustering analysis is conducted on each channel of the signals and multiple clustering results are counted and analyzed so that the optimal analysis result based on the prestack signals can be obtained, information of the prestack data can be fully utilized, and anisotropic characteristics of the signals are integrated into clustering judgments.

The invention provides a method for recovering a depositional sequence prototype section. Through sectional line drawing, splicing and combing of seismic reflection lineups, an upper super layer or a filling and supplementing interface serves as a horizontal reference layer, depositional environment information obtained by analyzing seismic facies is combined, and the continuing trend of a line drawn stratum is adopted, so that a depositional sequence is recovered to be at the depositional stage state. Through the sectional line drawing, splicing and combing of the seismic reflection lineups, namely reassembly, the sequence prototype section technology is obtained and named as the depositional sequence prototype section recovering technology through the seismic line drawing method. Through recovery of the depositional sequence prototype, the display degree of seismic data is improved greatly through arrangement of the stratum structure, the internal structure of a depositional system is clearer, and content needing displaying is more prominent.

The invention discloses a seismic phase feature recognition waveform inversion method based on a full convolutional neural network. The method comprises the steps of: preliminarily screening a seismicwave time window through a conventional seismic facies screening method FLEXWIN, manually screening data with higher quality as a training set, building a full convolutional neural network, and training the full convolutional neural network through the training set; performing seismic phase identification and window division on seismic waveform data by using the full convolutional neural network;and comparing the waveform similarity between the theoretic and observed data in the windows, and screening the waveform meeting the fitting condition to perform waveform inversion. Through a full convolutional neural network seismic phase feature recognition technology, the problem of efficient waveform window pickup in waveform inversion is solved, the problem of periodic jump is effectively improved, and the convergence rate of waveform inversion is increased.

The invention relates to a time-shifting-logging-based method for building an initial model with a seismic facies constraint. The method comprises: well seismic calibration is carried out by using an interpreting layer and data after time-shifting logging, a seismic spatial relation is established by combining seismic data, and a consistency analysis is carried out on a well seismic calibration result and the seismic spatial relation; a seismic data isochronal stratigraphic frame is established by using the interpreting layer and data after time-shifting logging, wherein the seismic data isochronal stratigraphic frame is established by carrying out guiding and tracking by using an inclination angle obtained by seismic calculation and subdividing a small layer; and on the constraint of the isochronal stratigraphic frame, interpolation is carried out by using the calibrated logging data and the seismic spatial relation to obtain an initial model. According to the invention, deposition distribution cab be reflected well and the basis can be established well for better and accurate inversion.

The invention discloses a reef reservoir engraving method. The method comprises a reservoir identifying step in which a reef reservoir growth layer is determined on the basis of single well facies analysis; a top-bottom engraving step in which the top-bottom of the reef reservoir is engraved on the basis of the growth layer and according to the seismic section and the wave impedance section of the reef reservoir; a top-bottom constraining step in which a plane growth favorable region of the reef reservoir is acquired according to the reef reservoir form, seismic facies data, sedimentary facies analysis and ancient landform analysis and further used to constrain top-bottom engraving so as to acquire a finely engraved top-bottom; and an internal structure determining step in which the internal structure and the geometric parameters of the reef reservoir are acquired by adjusting visualization parameters to perform visualization analysis on the reef reservoir on the basis of the finely engraved top-bottom. The method which can make the internal structure of the reef reservoir engraved achieves more comprehensive and more accurate engraving of the reef reservoir.

The invention discloses an RBM-based seismic prestack signal clustering method. Aiming at the characteristic of high dimensionality of seismic prestack signals, a dimension reduction method based on adepth limited Boltzmann machine network is introduced, a depth limited Boltzmann machine has relatively good abstraction feature extraction ability, and the output after dimension reduction can wellexpress an original signal. Aiming at the characteristic that the seismic signal is often noisy and hard to remove well, a fuzzy self-organizing neural network clustering algorithm is introduced, so that the seismic phase classification is expressed by membership degree; the information provided by the fuzzy classification result is more abundant and reasonable, so that the clustering result is more stable, and the classification result can be further explored. The method of the invention has lower computational complexity and can be popularized in large-scale seismic prestack data.

A method for identification and prediction of a fore-land basin extremely-thick conglomerate body belongs to the technical filed of petroleum and natural gas exploration and development. The method comprises the following steps: the step 1) determining electrical characteristics of a gravel layer; the step 2) determining the characteristics of gravel layer seismic horizon and seismic facies; the steps 3) carrying out electrical profile and earthquake depth profile superposition; and the step 4) carrying out gravel layer lithology and lithofacies space identification. The beneficial effects of the method are that gravel layer distribution range, lithology and lithofacies vertical and horizontal distribution rules and the like, which restrict fore-land basin oil and gas exploration and development at each geological time in the fore-land basin can be determined; speed traps caused by the gravel layers can be eliminated to the maximum degree; the earthquake processing imaging speed is allowed to be more accurate; seismic data quality reaches a new level; entrapment implement precision is improved greatly; and well exploration success rate can be further improved.

The present invention provides a foreland basin alluvial fan fine description and prediction method. The method comprises a step of establishing a foreland basin alluvial fan geological model, a step of establishing the stratigraphic framework of an alluvial fan, a step of carrying out seismic facies and attribute inversion to delineate the plane distribution range of an alluvial fan, a step of carrying out three-dimensional electrical inversion to divide the phase band boundary of the alluvial fan of each period, carry out the fine identification of internal lithology and lithofacies, and determine the spatial distribution characteristics of the lithology and lithofacies, and a step of applying OpenDtect software to analyze the alluvial fan vertical evolution and establishing the deposition model of a study area alluvial fan. The method provided by the invention is mainly based on the sedimentology theory and the geological model foundation established by alluvial fan exposure investigation, logging, seismic, electrical method and other materials are fully utilized, the means of logging geological interpretation, seismic sequence analysis, seismic facies interpretation, attribute analysis and electrical method interpretation are integrated, and each phase band of the alluvial fan and the internal lithology and lithofacies spatial distribution characteristic are effectively identified.

The invention relates to a reservoir prediction method under a less well condition. The method comprises the following steps of acquiring the logging data and the seismic data of an exploration target, carrying out three-dimensional interpretation tracking on the seismic data of the exploration target, and acquiring the geologic horizon interpretation result of the exploration target; qualitatively dividing the typical measuring line seismic facies of the exploration target; quantitatively dividing the seismic facies of the three-dimensional seismic data volume of the exploration target; carrying out sedimentary facies interpretation on the quantitatively-divided seismic facies of the three-dimensional seismic data volume of the exploration target and acquiring the macroscopic reservoir distribution trend understanding of the exploration target; determining the types of reservoir sensitive parameters which can reflect reservoir characteristics and the numerical range of the reservoir sensitive parameters which can reflect the reservoir characteristics corresponding to a reservoir; calculating the values of the reservoir sensitive parameters which can reflect the reservoir characteristics; extracting a reservoir sensitive parameter attribute plane graph; and re-delimiting the numerical range of the reservoir sensitive parameters which can reflect the reservoir characteristics corresponding to the reservoir in the reservoir sensitive parameter attribute plane graph and then predicting a reservoir distribution rule.

The invention belongs to the technical field of uranium mine exploration and particularly relates to a method for predicting an ancient valley uranium reservoir by using old seismic data. At present,the main prospecting means and method are drilling, but investment cost is high, the period is long, and a traditional method is difficult to predict the ancient valley uranium reservoir. The method mainly comprises steps of step 1, determining uranium reservoir attributes by utilizing known uranium mine geological drilling data through a construction criterion, a uranium source criterion, a lithology-lithofacies criterion and a rock geochemistry criterion; 2, combining a petroleum two-dimensional seismic section, carrying out fidelity amplitude preservation processing of anterior seismic data, highlighting the shallow seismic reflection information, analyzing an ancient valley seismic facies of a seismic section passing through a known uranium mine hole, carrying out wave impedance inversion according to known well wave impedance and seismic wave spectrum analysis, realizing shallow interpretation and structure identification of a petroleum seismic section, and determining uranium reservoir attributes; and 3, performing combined verification. The method can be used for predicting the ancient valley uranium reservoir.

The present invention relates to a method for identifying a weak reflection reservoir. Firstly, according to a formation lithology structural characteristic, the geological factors of seismic weak reflection lithology oil reservoir formation is determined through forward modeling, then seismic data is subjected to frequency extraction and filtering process so as to improve the identification ability of a weak reflection small size target by earthquake, then the seismic facies analysis is carried out, a seismic weak reflection development zone is determined, seismic attribute analysis is carried out, the distribution characteristics of the weak reflection reservoir is finely described, and the weak reflection reservoir is identified through the seismic weak reflection development zone and the reservoir distribution characteristics obtained according to the seismic facies and the seismic attribute. The identification and hydrocarbon potential detection are carried out through wavelet decomposition and reconstruction, the precision of reservoir prediction and trap identification are improved, and the purpose of improving the success rate of drilling is achieved. According to the method, the precision of weak reflection geological target identification and fine description are effectively raised, the method is systematic, effective, economical and practical, and the method is widely applied to the oil and gas exploration under the same geological conditions and has good social and economic values.