114 results about "Cross-plot" patented technology

A signal processing system and method for breaking a time series into piece-wise discrete trends and determining whether new data represents the continuation of a trend. The method identifies and utilizes at least one set of trend determination parameters, which have favorable trend fit characteristics relative to other possible sets of parameters. In a semi-automated embodiment, the error and trend length characteristics are cross-plotted for multiple sets of possible parameters, and one or more of the parameter sets is selected from the graph. In an automated embodiment, an objective function is formulated from the characteristics, and an optimization technique is applied to identify one or more good parameter sets.

Monitoring events triggered by a computer network. Each event being provided with attribute values allocated to a given set of attributes, and providing an event display, determining a primary attribute and a corresponding display label of the events selected from the given set of attributes presented with attribute values on a cross plot, providing a pattern algorithm to detect whether an arrived event is part of a given pattern, providing a mapping algorithm to map attribute values on the cross plot, allocating a second display label to the events indicating the attributes uncovered as part of the given pattern, plotting events arriving and including an attribute value allocated to a primary attribute into the cross plot, and plotting events arriving within the time period and detected by the pattern algorithm as part of the given pattern into the cross plot with the second display label indicating the given pattern.

The invention provides a seismic reservoir prediction method by cross analysis based on target analysis. The method comprises the following steps of: carrying out attribute calculation and back calculation on original seismic data so as to obtain seism preparation data for seism reservoir prediction and preparation data for well measurement; carrying out the cross analysis on well measuring data, thus determining whether a reservoir section on a cross plot of the well measuring data has obvious characteristics; and if so, defining a rational seismic reservoir prediction result according to the scope of parameters obtained from the cross analysis on the well measuring data and the existing data.

The invention discloses a method for identifying water logging grades of an oil reservoir by using a neural network analogue cross plot. In the method, the conventional cross plot technology is improved by a neural network algorithm, so nonlinear identification and quantitative analysis functions of the cross plot are realized, and a back propagation (BP) neural network algorithm is used and the method comprises the following steps of screening object characteristic parameters, selecting network structure parameters, training a neural network model, testing the network model, and establishing a neural network analogue cross plot layout. The method specifically comprises the following steps of: according to various characteristics of oil, gas and water layers in reservoirs, accurately selecting parameter samples which can best reflect the characteristics of the oil, gas and water layers in the reservoirs from parameters calculated during well logging or the well logging curves relevant to oil and gas interpretation by a statistics method; selecting appropriate weight values and threshold values by the BP neural network algorithm to establish the network model, and training the model and checking errors; and judging the fluid type or water logging degree of the reservoir with the depth according to projective points of identification vectors which are obtained by network output on a plane.

The invention relates to a beach bar structure unit discrimination method under the constraint of a geological model. The development process of a beach bar is divided into four stages, and five sedimentary structure units are subdivided. The correspondence between four stages and five units is determined. Twelve electrical imaging modes corresponding to five structure units are set up. The conventional logging curve characteristic of each structure unit is summarized. A conventional logging curve with strong sensitivity is selected through a cross plot analysis method. According to a Bayes discrimination method in discrimination analysis and according to the mutual superimposition relationship between the sedimentary units in a vertical profile, the sedimentary type and the evolution stage of the beach bar are determined. According to the invention, the reasonable and effective constraint of the geological model is used; the electrical imaging modes and the conventional logging curve characteristic of each structure unit of the beach bar are combined; according a Bayes discrimination principle, the conventional logging curve with strong sensitivity is selected to establish a discrimination formula; on the basis of the discrimination formula, calculation is carried out; the structure units are accurately and rapidly identified; and the discrimination accuracy is improved.

The invention discloses a method (Ip) for evaluating the properties of a reservoir based on gas survey logging data. The method comprises the following steps of: 1) defining Ip series indexes; 2) making an Ip cross plot, and counting data points in the chart of the Ip series indexes; and 3) drawing an explanatory drawing by the Ip series indexes corresponding to a well depth. In conclusion, the technical problem to be solved by the invention is to provide a novel method for explaining the properties of a gas ratio reservoir based on the gas survey logging data; an original Pixler chart method is greatly reformed; novel evaluation indexes are calculated; a novel explanatory chart is established; and a drawing application form is explained. The quantized Ip series indexes can be combined with other gas survey parameters and even with logging parameters, thereby being flexible in use and providing convenience for the evaluation of a hydrocarbon reservoir.

The invention provides a lacustrine facies peperite reservoir logging recognition method based on composition-structure classification. The method includes the steps of sample acquisition, wherein lithological standardization base data and a corresponding conventional logging curve are acquired; curve-sample lithological standardization, wherein a logging curve in a corresponding well section is extracted according to the lithological standardization result; sample classification, wherein known lithological samples are classified according to compositions and structures; lithological composition-structure indication sensitivity curve optimization, wherein a box figure method and a cross plot method are adopted as optimization methods; establishment of a composition-structure secondary classification lithological interpretation flow chart according to the optimization result; lithological recognition on unknown lithological sections according to the lithological interpretation flow chart. The conventional logging curve is used for qualitatively recognizing rock compositions and structures of a lacustrine facies peperite reservoir, rock types are conveniently and accurately recognized, and base data is provided for following logging comprehensive interpretation, formulation of test measures in shaft operation and lithological calibration of sections in which rock (walls) cores are not taken.

An embodiment of the invention provides a well logging curve correction method and device. The method includes: acquiring straight well section depth values and well logging values of multiple collection points of a straight well section according to formation interface information at a locus of a horizontal well section, horizontal well section information and straight well section information, and acquiring horizontal well section depth values, well logging values and well drift angles at positions, corresponding to the collection points on the straight well section, of the horizontal well section according to the straight well section depth values; acquiring a correction function fitting relation through cross-plot fitting according to the well logging values and the well drift angles of the horizontal well section and the well logging values of the straight well section; correcting a well logging curve of the horizontal well section according to the correction function fitting relation. The formation interface information at the locus of the horizontal well section is fully utilized, so that the problem that existing well logging curve correction methods do not fully utilize transverse information of a horizontal well and are low in correction accuracy is solved, accuracy and reliability of correction are improved, and simple, quick, practical and effective correction of the well logging curve is realized.

The invention discloses an oil and water layer recognition method suitable for a volcanic reservoir. The oil and water layer recognition method comprises the following steps of performing inversion processing on an echo string by using nuclear magnetic logging data in a dual waiting time mode to obtain a long waiting time T2 spectrum and a short waiting time T2 spectrum; then performing differential spectrum processing to obtain a difference spectrum reflecting oil and gas information; performing integral processing on the difference spectrum to obtain difference spectrum porosity (Diff_Por); determining sensibility of various hydrocarbon components on an oil and water layer by gas logging data establishing a hydrocarbon characteristic ratio (Ratio_C); establishing a cross plot of the difference spectrum porosity and the hydrocarbon characteristic ratio according to existing oil testing data and determining a distinguishing boundary of the oil and water layer; extracting the difference spectrum porosity and the hydrocarbon characteristic ratio of a stratum of which oil and water are about to be recognized according to the previous steps; and effectively recognizing the oil and water layer by using the established cross plot. On the basis of nuclear magnetic differential spectrum processing, processing is carried out further to obtain the difference spectrum porosity, the cross plot is established by the difference spectrum porosity and the hydrocarbon characteristic ratio obtained by the gas logging data, and then the oil and water layer of the volcanic reservoir can be recognized.

The invention relates to a determination method of organic porosity of a shale gas reservoir based on well logging data. The method comprises following steps: collecting shale gas reservoir organic porosity data and shale gas reservoir well logging data obtained through work area parameter well core experimental analysis; calculating inspected organic matter maturity Roa1 of the parameter well shale gas reservoir; calculating organic porosity [phi]toca1 of the parameter well inspected shale gas reservoir; obtaining organic porosity coefficient K of the work area shale gas reservoir by means of the cross-plot technology; collecting well logging data of the shale gas reservoir to be processed; calculating the reservoir inspected organic matter maturity Roa; calculating the organic porosity [phi]toca of the inspected shale gas reservoir of the well to be processed; calculating the organic porosity [phi] toc of the gas reservoir; outputting the calculation results of the organic porosity [phi]toc of the shale gas reservoir of the well to be processed. By means of the method, reliable data is provided for shale gas reservoir evaluation and prediction rate is increased. The method is simple and has wide application scope. The method is applied in 182 wells in Fuling shale gas field, and the prediction rate is high.

The invention provides a well circumference interface detection method based on electromagnetic scattering. The method comprises the following steps that symmetrical antenna structures are utilized to extract scattering field signals, and characterization is conducted on the well circumference interface by gaining difference signals; the relations between the boundary exploration capacity and the transmitting frequency, the boundary exploration capacity and the source distance as well as the boundary exploration capacity and the tilt angle are determined, and suitable parameters are chosen to achieve the optimum detection effect; and a single-shot four-receiving antenna structure is adopted for detection, and the cross-plot identification interface relative position is established. According to the well circumference interface detection method, the influence of an electromagnetic scattering field on the well circumference interface detection effect is sufficiently considered, the amplitude difference of symmetrical receiving antennas is utilized to show electromagnetic scattering signals, rapid identification of the well circumference interface is achieved, and combination of the two sets of antenna structures is utilized to complete determination of the well circumference interface relative position; and the identification method is simple, and the effect is obvious.

The invention relates to a tight sandstone fluid type identification method based on a support vector machine simulation cross plot. Parameters best reflecting oil gas and water layer characteristics in a reservoir layer are firstly selected to be taken as fluid sample data; a support vector machine algorithm is applied then, and a proper penalty parameter and a proper kernel function are selected to construct a classification prediction model; vector data points obtained by the classification prediction model are projected to a cross plot plane so that a support vector machine simulation cross plot plate is formed; and to-be-recognized sample data are input into the support vector machine simulation cross plot plate to form projection distribution points, distances between the various projection distribution points and various fluid type center points in the support vector machine simulation cross plot are calculated, and the fluid type represented by a shortest-distance center point is taken as a to-be-identified fluid type. The method can integrate multiple characteristic parameters of research objects to perform accurate division on types of the objects, and limitation that the cross plot only can integrate two characteristic parameters to perform type division is made up.

The invention provides a method and a device for determining tuffaceous contents by means of elementary capture energy spectrum well logging, and belongs to the technical field of oil and gas exploration well logging. The method includes reconstructing real natural gamma well logging response curves of to-be-logged wells according to elementary capture energy spectrum well logging curves; comparing the real natural gamma well logging response curves with measured natural gamma well logging response curves to obtain layer sections of tuffaceous components; creating cross plots of the measured natural gamma well logging response curves and products of thorium curves-compensate neutron well logging curves; determining the tuffaceous contents according to locations of sample points of the measured natural gamma well logging response curves in the cross plots. The method and the device have the advantages that the cross plots of the measured natural gamma well logging response curves and the products of the thorium curves-compensate neutron well logging curves are created, the tuffaceous contents are determined according to regions of the sample points of the measured natural gamma well logging response curves in the cross plots, and accordingly obtained results are high in accuracy and precision and good in applicability.

The invention relates to a method for calculating wellbore water-holding capacity and formation water saturation in RPM well logging. The method comprises the steps that a regular chart of the changes of the carbon-oxygen ratio along with formation porosity in RPM well logging is obtained only considering the sizes of a wellbore and a casing pipe; a carbon-oxygen ratio calculation formula is obtained according to the sizes of the wellbore and the casing pipe in RPM well logging; the carbon-oxygen ratio in RPM well logging is obtained when water filling is conducted on a wellbore water filling formation and oil filling is conducted on a wellbore water filling formation; the carbon-oxygen ratio in RPM well logging is obtained when oil filling is conducted on a wellbore oil filling formation and water filling is conducted on a wellbore oil filling formation; carbon density and oxygen density of water in the wellbore and carbon density and oxygen density of oil in the wellbore are calculated; the carbon-oxygen ratio in RPM well logging is calculated when influence factors comprise the wellbore, the casing pipe and gravel; the carbon-oxygen ratio in RPM well logging is calculated when the influence factors comprise the wellbore, the casing pipe, the gravel and mud; the carbon-oxygen ratio in RPM well logging is calculated when influence factors comprise the wellbore, the casing pipe, the gravel, the mud and calcium; a cross plot of near-far carbon-oxygen ratio is built; the wellbore water-holding capacity and the formation water saturation are obtained according to the cross plot of the near-far carbon-oxygen ratio.

The embodiment of the invention provides a method and apparatus for predicting a tight gas layer based on frequency-variable reflection amplitude attenuation. The method comprises the following steps:analyzing the range and characteristic frequency of oil and gas reservoir attenuation along with frequency changes; determining pore elastic parameters of a cover layer, an oil and gas reservoir anda water layer; forward modeling attenuation characteristics of the reflection amplitude of the oil and gas reservoir or the water layer along with the offset or the incident angle under different frequency conditions; performing calculation to obtain a pre-stack time-frequency data volume in an effective frequency range; determining an offset range in which the amplitude frequency change of the oil and gas reservoir changes drastically; calculating a pre-stack reflection amplitude attribute parameter AMO according to the offset distance or incident angle determined by a cross plot in combination with a frequency-varying reflection amplitude forward modeling result; and according to a low-frequency attenuation attribute parameter AAI and a high-frequency attenuation attribute parameter AAI,calculating a pre-stack reflection amplitude attenuation index parameter FDAAI depending on frequency changes, determining an FDAAI profile, and carrying out position identification on the oil and gas reservoir, so that the tight gas reservoir can be accurately identified.

The invention relates to a well logging method for rapidly determining the content of biological silicon in graptolite facies heat shale. The well logging method comprises the following steps: acquiring TOC (Total Organic Carbon) measured data of the well graptolite facies heat shale and acquiring SiO2 measured data of the well graptolite facies heat shale; selecting a data sample according to a depth corresponding relationship and drawing a TOC-SiO2 cross plot, wherein A and B are the slope of a regression straight line and the intercept on the Y axis; establishing a linear regression equation SiO2 being equal toA*TOC+B which takes TOC as an independent variable and SiO2 as a dependent variable; solving a correlation coefficient R by utilizing a least squares linear regression method; judging a correlation relationship between the independent variable TOC and two variables and directions by utilizing the R; when the R is greater than or equal to 0.7, characterizing positive correlation and entering the next step; when the R is less than 0.7, returning; calculating the content of Si_toc of the biological silicon by utilizing an equation Si_toc being equal to 0.47(SiO2-B) and outputting a result. The well logging method provided by the invention is applied to more than 120 wells and the error is less than 15 percent; the speed is rapid and the cost is low.

The invention relates to a method for predicting a thin layer thickness by the utilization of a time-frequency spectrum cross plot changing along with geophone offsets. According to the method, time-frequency spectrum decomposition is performed on a trace gather to obtain a date cube, and the ranges and time window lengths of the near geophone offset and the middle-far geophone offset are selected; integral multiples of frequencies are used for fetching data out to form a time-frequency spectrum of the near geophone offset and a time-frequency spectrum of the middle-far geophone offset, and the time-frequency spectrum of the near geophone offset and the time-frequency spectrum of the middle-far geophone offset are crossed to form the time-frequency spectrum cross plot changing along with the geophone offsets; logging data are firstly used for synthesizing seismic forward modeling trace gathers different in thin layer thickness, and a time-frequency spectrum cross plot of the forward modeling trace gathers is used; the time-frequency spectrum cross plot of the field trace gather is compared with the time-frequency spectrum cross plot of the forward modeling trace gather, so that the thin layer thickness of underground media is obtained. The new method is used for predicting a thin layer of which the thickness is smaller than quarter of wavelength.

The invention relates to a method for determining a stratigraphic sequence interface by utilizing interval transit time, which comprises the following steps: acquiring a logging value of an acoustic curve in a logging curve; displaying an acoustic value of the logging curve in a logarithmic form; drawing a cross plot by using depths and interval transit time values in the form of logarithm; and identifying the sequence interface according to the change rule of the curve in the cross plot above and below the sequence interface. According to the method, the sequence interface is identified according to the abnormal conditions of the interval transit time corresponding to different depth points; parameter selection is visual and reliable, and function conversion is not needed, thus convenience and objectivity of sequence interface identification are greatly improved.

The invention provides a method and a system for quickly identifying lithology based on a cross plot method. The method comprises the steps of S01, selecting a logging interpretation series; S02, normalizing logging data; S03, finely identifying lithology by using a two-step lithology identification method; S04, determining the lithology boundary and the lithology type by performing statistical analysis on data of different lithology types and comparing the frequencies of different lithology types; and S05, judging and identifying lithology. According to the invention, lithology of a researcharea is analyzed, and a new thought, method and mode are used to quickly determine lithology. On the basis of reserving simple use, data graphical representation and rapid and intuitive lithology identification of the cross plot method, the problem that the cross plot method is difficult to use and cannot reach the standard of fine lithology identification when there is only a small number of rockcores, slices and logging data is solved, and lithology identification is carried out on a large number of logging data by utilizing the model.

The invention relates to a method for quantitatively evaluating 3D seismic attribute reservoir parameter prediction effectiveness. The method comprises the following steps: according to the well-seismic time-depth calibration result, extracting same-algorithm and different-type seismic attributes and attribute values of drilled well coordinates; combined with reservoir parameters formed based on reservoir identification standard, establishing a cross-plot pattern and carrying out linear fitting to determine a correlation coefficient, and preferably selecting an effective seismic attribute typeaccording to the correlation coefficient; on the basis of making clear the effective seismic attribute type, extracting same-type and different-algorithm seismic attributes and attribute values of drilled well coordinates; establishing linear fitting relationship with the reservoir parameters again; and taking the correlation coefficient as basis for quantitative evaluation of seismic attribute reservoir parameter prediction effectiveness. The method, through two intersection fitting, makes clear the optimal attribute type and a corresponding optimal calculation method as the basis for quantitative evaluation of 3D seismic attribute prediction effectiveness, thereby reducing later risk of new drilling deployment.

A method for predicting jumps in pore pressure of a subsurface includes the steps of obtaining a porosity and a resistivity log value while drilling; dividing a cross plot of the porosity and the resistivity log values into two regions where the split of the two regions is based on the following (I): R=0.062/ø^1.5; averaging the obtained porosity and resistivity log values in the subsurface within a set interval to obtain a representative value of resistivity and porosity for the subsurface within the set interval; and giving a first warning of a high overpressure region if the representative value of resistivity at the representative value of porosity is lower than 0.062/ø^1.5. The method may also include giving a second warning that a jump in pore pressure is coming within 100-300 meters if the normalized values of resistivity and porosity has a turning down point in its trajectory.