CN102053268B - Method and device for identifying lithologic character of altered volcanic rock - Google Patents

Abstract

The invention relates to the field of geological exploration, particularly to a method and a device for identifying the lithologic character of altered volcanic rock. The method comprises the following steps: the relation between the lithologic character of volcanic rock and the corresponding drilling-logging data is established; lithologic character parameters are extracted from the drilling-logging data relating to the lithologic character of the volcanic rock; the extracted lithologic character parameters undergo information fusion, so as to obtain the feature model for drilling and logging the lithologic character of the volcanic rock; the measuring parameters of the volcanic rock to be measured before the drilling-logging are obtained; the measuring parameters of the volcanic rock to be measured are combined to a group identical with the character parameters in the information fusion, so as to be matched with the feature model; and if the matching is successful, the lithologic character of the volcanic rock corresponding to the volcanic rock to be measured is output. The embodiment of the invention can be used for visually, correctly, quickly and effectively identifying the lithologic character of the volcanic rock, and especially the knowledge on the altered volcanic rock is remarkably improved.

Description

A kind of alteration Lithology Identification Methods for Volcanic Rocks and device

Technical field

The present invention relates to geological exploration field, particularly about a kind of alteration Lithology Identification Methods for Volcanic Rocks and device.

Background technology

Existing more than the 100 year history of volcanics research, lithology identification basis is the volcanics lithology breakdown, mineral content, chemical constitution, the place of production and structure, structure all are the foundations of pyrogenic rock classification name.Owing to the difference of each family's classification starting point, add the diversity of volcanics itself, cause existing volcanics title to reach kind more than 1000.Though this has reflected the complicacy of volcanics and various fact, also show the confusion that human factor causes in the classification name.With the polarizing microscope is basic tool; The petrographic thin section that is characterized as appraisal basis with the mineral photosensitiveness identifies it is the basis of confirming volcanic rocks classification, lithology, sets up the key that volcanics alteration pattern is lithology identification from lithochemistry component, origin mechanism and evolution rule.Along with going deep into of volcanics oil-gas exploration and development, the exploitation of deep volcanic rock reservoirs exploration receives publicity day by day.Because deep volcanic rock reservoir lithology, fluid composition are complicated and changeable, crystallization degree difference is big, brings great difficulty to evaluation of volcanic rock reservoir.Confirm accurately that wherein the volcanics lithology is carry out the work of volcanic rock reservoir studies basic and crucial.

To volcanics lithology Difficulties of Identification; Carried out the research of a large amount of relevant volcanics lithology identification aspects both at home and abroad; Formed such as the TAS figure method of capturing well logging (ECS) based on element, structure method of identification, neural network method and the combined recognising method thereof of electric imaging logging, like the three-dimensional Lithology Identification Methods that combines with ECS and electric imaging logging.To the volcanics lithology identification volcanics lithology identification thinkings that adopt the lithochemistry component to combine, confirm the volcanics lithology at present with structure more.In volcanics lithology breakdown and Study of recognition; The volcanics TAS figure sorting technique that international ground section joins (IUGS) recommendation is only applicable to fresh volcanics classification; Because the ancient volcanics of deep layer all can receive alteration transformation in various degree behind diagenesis, research shows, after the volcanics alteration (comprising hypergene weathering eluviation and diagenesis later hydrothermal alteration); The physicochemical property of rock (component, structure, structure, color, hardness, electrically, drillability etc.) can take place significantly to change; Though alteration volcanics lithology identification problem has many-sided research, is confined to experimental analysis more, makes slow progress generally.Current paper and patent retrieval show: still form the effective ways and the special system tool of discerning the alteration volcanics that utilize well information to carry out the identification of alteration volcanics lithology.

Summary of the invention

The embodiment of the invention provides a kind of alteration Lithology Identification Methods for Volcanic Rocks and device, is used for solving prior art alteration volcanics lithology identification complicacy, and inaccurate problem.

The embodiment of the invention provides a kind of alteration Lithology Identification Methods for Volcanic Rocks in order to solve the problems of the prior art, comprising:

In boring record well logging process, also comprise the volcanics rock core is carried out analysis of chemical elements, and set up the related of volcanics lithology and element chemical analysis data;

In the brill record log data related, extract characteristic parameter with said volcanics lithology;

The characteristic parameter of said extraction is carried out information fusion; Comprise in the characteristic model of acquisition volcanics lithology: with said characteristic parameter generating feature parametric line; Volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing through scale, and gives corresponding RGB color value said standardized curve each point; Calculate the rgb space eigenwert according to the RGB color value, length that said space characteristics value is the rgb space vector and RGB solid space volume are neglected the cube eigenwert greatly; Described RGB color value is fused into the chromatogram on the depth-logger; Set RGB according to the rgb space eigenwert of correspondence again and merge the width that shows; Obtain the characteristic model of said volcanics lithology, set up the mapping of boring record logging operation parameter with said characteristic model accordingly;

In addition, obtain in the measurement parameter of volcanics to be measured in boring the record well logging, treat the survey volcanics and detect, obtain the lithologic parameter of this volcanics through physics and/or chemical means;

With the measurement parameter of said volcanics to be measured form with said information fusion in the identical combination of characteristic parameter, mate with above-mentioned characteristic model;

If mate successfully, then the output volcanics lithology corresponding with said volcanics to be measured also exported the corresponding said brill record logging operation parameter of this volcanics to be measured.

The embodiment of the invention also provides a kind of alteration volcanics lithology recognition device, comprising:

Associative cell, characteristic parameter extraction unit, information fusion unit, measuring unit, matching unit, output unit;

Said associative cell is used to set up the volcanics lithology and records the related of log data with corresponding brill;

Said characteristic parameter extraction unit is used for extracting characteristic parameter in the brill record log data related with said volcanics lithology;

Said information fusion unit is used for the characteristic parameter of said extraction is carried out information fusion, obtains the characteristic model of volcanics lithology;

Said measuring unit is used for obtaining volcanics to be measured at the measurement parameter that bores the record well logging;

Said matching unit is used for the measurement parameter of said volcanics to be measured is formed and the identical combination of said information fusion characteristic parameter, matees with above-mentioned characteristic model;

Said output unit is used for exporting the volcanic rock lithological information corresponding with said volcanic rock to be measured when the match is successful.

Pass through the embodiment of the invention; To volcanics lithology identification have intuitively, accurately, characteristic rapidly and efficiently; Particularly the understanding to the alteration volcanics obtains to significantly improve, and with drilling and coring delivery, the contrast of sidewall sampling lithology qualification result, alteration volcanics lithology recognition accuracy reaches more than 93%.

Description of drawings

In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art; To do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below; Obviously, the accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills; Under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.

Shown in Figure 1 is the process flow diagram of a kind of alteration Lithology Identification Methods for Volcanic Rocks of the embodiment of the invention;

Shown in Figure 2 is SiO after the alteration of embodiment of the invention typical case volcanics ₂Middle changes of contents figure;

Shown in Figure 3 is thorium (Th) in the fresh slag of the embodiment of the invention-potassium (K) graph of a relation;

Shown in Figure 4 is thorium (Th) in the fresh slag of the embodiment of the invention-uranium (U) graph of a relation;

Shown in Figure 5 is elemental iron in the embodiment of the invention volcanics (Fe)-elemental silicon (Si) massfraction graph of a relation;

Shown in Figure 6 is the synoptic diagram of the characteristic model of embodiment of the invention volcanics lithology;

Shown in Figure 7 is the embodiment of the invention is calculated the rgb space eigenwert according to the RGB color value principle schematic;

Shown in Figure 8 is the structural representation of a kind of alteration volcanics of embodiment of the invention lithology recognition device;

Shown in Figure 9 is that a kind of alteration volcanics of embodiment of the invention lithology RGB merges and fusion spatial parameter figure.

Embodiment

To combine the accompanying drawing in the embodiment of the invention below, the technical scheme in the embodiment of the invention is carried out clear, intactly description, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills are not making the every other embodiment that is obtained under the creative work prerequisite, all belong to the scope of the present invention's protection.

Be illustrated in figure 1 as the process flow diagram of a kind of alteration Lithology Identification Methods for Volcanic Rocks of the embodiment of the invention.

Step 101 is set up the volcanics lithology and is recorded the related of log data with corresponding brill.

Wherein, bore the well data in the record log data, come from some record data that in drilling process, produce, time for example, the pressure of drill bit, the rotating speed of drill bit, the density of mud; Logging data, measurement and record that the rock chip taken out of in the drilling process and rock fluid are carried out, the color of rock chip for example, size, the density of particle etc.; Log data, under the instrument lower going-into-well, physics, chemical measurement to carry out the lithostratigraphy for example carry out measurements such as radioactivity, density, sound wave, resistivity.

The described volcanics lithology of setting up is meant with corresponding brill record the related of log data; Set up the corresponding relation between the data that volcanics that rock core research named and this volcanics produce in boring record well logging process, during like the corresponding low brill of ryolite, lighter color, low-density, high natural gamma, high resistivity; Darker, the high neutron of alteration andesite corresponding color, low-resistivity, low uranium, low thorium etc.Here high and low produces data in boring the record well logging all have concrete data.

Mate the degree of depth of drilling well rock core collection and the degree of depth of boring the record well log measurement; Read the brill record Well logging Data of the corresponding degree of depth of rock core; Utilize analysis different lithology such as crossplot analysis and its method, statistical analysis method, theoretical analysis the volcanics lithology of naming and the correlativity and the degree of correlation of boring the various data of record well logging, example is as shown in table 1:

Table 1

In this step, also comprise, the volcanics rock core is carried out analysis of chemical elements, set up the related of volcanics lithology and element chemical analysis data.

Can know down that to mirror discerning the volcanics of adding up mineral names according to volcanic rocks credit class standard, is converted into the massfraction classification indicators with mineral volume fraction sorting parameter; For phanerocrystalline-adiagnostic or miocrystalline volcanics; Need be by total rock chemical analysis means; Carry out the volcanics category name according to main oxides content analysis result and TAS figure; Be that full alkali-silica component is named, component is named requirement and must be selected fresh volcanics to analyze, and will provide SiO to the alteration volcanics ₂Utilize TAS figure to carry out the volcanics category name after the correction of content because of the alteration variation again; Directly adopt element quality (weight) mark to carry out lithology identification to alteration volcanics and nonacid volcanics; Do not adopt the TAS figure method lithology breakdown on the oxides closure The model calculation basis, to reduce the lithology identification error that closed effect is brought.

Step 102 extracts characteristic parameter in the brill record log data related with said volcanics lithology.

Selection and lithology correlativity, the brill that susceptibility is good are recorded log data as the rock signature parameter; To dissimilar volcanics characteristic parameter separately can be arranged respectively; Select the most characteristic monistic rock signature parameter that has; For example, acid slag has high natural gamma (GR), and curve is straight; High resistivity (RT), curve is straight; Low-density (DEN), lithology sensitive parameter such as curve is straight.Said correlativity is meant that brill is recorded log parameter and the lithology correlativity is good, and susceptibility is meant along with lithological change parameter also marked change.

Lithology according to volcanics; Select to bore record WELL LITHOLOGY susceptibility rule notable attribute curve; Implement forward sensitivity (as along with the acid enhanced natural gamma of volcanics (GR) significantly increases), anti-(bearing) to responsive (reducing) as strengthening density (DEN) log value along with volcanics is acid; Linearity, logarithm, statistical probability accumulative total sensitivity, the perhaps variable brill record log data that is changed to quantitative sensitivity.For example conventional clastic sedimentary rock lithology sensitivity curve mainly contains natural gamma (GR), hole diameter (CAL), spontaneous potential (SP); The rerum natura sensitivity curve mainly contains interval transit time (AC), lithology and density logging (DEN), compensated neutron (CNL); Electrically sensitivity curve mainly contains formation resistivity (RT), invaded zone resistivity (RI), flushed zone resistivity (RXO) etc., qualitative, quantitative examination affirmation that the susceptibility rule of various curves needs.Concrete research method can be used conventional logging crossplot analysis and its method, frequency statistics method, theoretical analysis etc.

Well data mainly reflects rock drillability, hardness, rub proofness, rerum natura etc.; Well logging can reflect color, density, grain size, gas bearing condition of rock etc.; Log data can measure the radioactivity, stress characteristics, factor of porosity of rock, electrically, constituent content, rock texture etc., different rocks different to boring the susceptibility that record surveys parameter.Characteristic parameter can be based upon known definite lithology and analyze the back extraction with boring on the record log data basis through being familiar with after the manual analysis; Also can record on the logging character parameter basis and can select automatic extraction at the brill of knowing lithology in advance; Automatically extraction can be adopted the characteristic parameter that related coefficient is big, susceptibility is good; Be that the measurement parameter variation that lithological change causes is the bigger the better; For example can set threshold value, when the parameter of boring the record well logging surpasses threshold value (like confidence level R to characteristic parameter ²＞0.7) thinks that then this parameter meets the requirement of lithology relevant sensitization, can be used as characteristic parameter.

The characteristic parameter of alteration volcanics and non-alteration volcanics is different, and for example shown in Figure 2 is SiO after the typical volcanics alteration ₂Middle changes of contents figure, SiO after the acid volcanic rock alteration during this figure shows ₂The changes of contents scope is bigger, compares SiO with fresh volcanics ₂Content can not simply use SiO as the unique conditional of alteration volcanics lithology identification ₂Content changes in the alteration process, the standard applicability variation of naming as lithology, but still the identifying feature parameter that can be used as the alteration volcanics uses, under the identical alteration environment, the lithology alteration is similar, SiO ₂The changes of contents measurer is regular, and the identification of TAS figure method lithology is not suitable for the alteration volcanics.

Be illustrated in figure 3 as thorium in the fresh slag (Th)-potassium (K) graph of a relation, this figure shows along with volcanics is acid to be increased, and Th and K are the index positive correlation, if the imbalance of Th-K relation is generally alteration features, wherein R ²Correlativity (square R of coefficient R for Th and K ²Be called definite coefficient, can confirm the probability of dependent variable exactly with independent variable), y is independent variable curve (Th); Shown in Figure 4 is thorium in the fresh slag (Th)-uranium (U) graph of a relation, and this figure shows along with volcanics is acid to be increased, and Th and U are linear positive correlation, if the imbalance of U-Th relation is generally weathering leaching characteristic, wherein R ²Be the correlativity of Th and U, R ²Can calculate according to the Excell correlation analysis and through least square method; Y is independent variable curve (Th), if depart from the intrinsic relation that this figure sets up, can be judged to be weathering, alteration; It or not fresh volcanics; Two measured values that are associated keep intrinsic relevance (can be used as alteration volcanics characteristic parameter with the degree of deviation), can be used as normal volcanics criterion, depart from then as the criterion of alteration volcanics; Shown in Figure 5 is elemental iron in the volcanics (Fe)-elemental silicon (Si) massfraction graph of a relation; This figure shows along with volcanics is acid to be increased; The Si element increases and the minimizing of Fe element; This figure has provided volcanics component characteristics scope, can confirm acid volcanic rock, neutral volcanics, basic volcanic rocks according to Fe, Si content range, and wherein the content range of Fe, Si can be characteristic parameter.The susceptibility of which parameter was relatively good when above-mentioned accompanying drawing illustrated lithology identification, was the key experimental basis of selecting characteristic parameter to analyze.

Step 103 is carried out information fusion with the characteristic parameter that extracts, and obtains the characteristic model of volcanics lithology.Can also set up the mapping of boring record logging operation parameter with said characteristic model accordingly, said operating parameter can be for example for to the drilling speed of the volcanics drill bit of certain lithology, pressure or the like.

Curve negotiating scale that above-mentioned characteristic parameter is constituted or SSization are converted into the have identical qualitative sensing standardized curve of (just focusing on), give corresponding RGB color value with said standardized curve each point.

Step 1031, the curve that characteristic parameter is constituted focuses on planning formation standardized curve, that is to say; Three characteristic parameter curves such as V1 (0～255), V2 (1000～1255) are for example arranged; V3 (300～810) is through becoming after the scale meritization: R (V1) (0～255), G (V2) (0～255), and B (V3) (0～255), wherein R is red; G is green; B is blue, and 0～255 be that the RGB component of each pixel in the image distributes one 0～255 intensity level in the scope, and characteristic parameter curve numerical value change has jointly directive property and is called to focus on and plans behind this planning scale; Focus on planning and can be divided into planning such as linearity, logarithm or statistical probability, set according to sensibility analysis rule result to characteristic parameter.Wherein, focusing planning realizes the conversion of characteristic parameter, becomes with lithological change measurement focusing parameter to have single sensing regularity.Any metrical information all not only reflects single character, and the multi-solution of information just is this, and many information fusion can be dwindled the common factor of information, reduces the multi-solution of information; It doesn't matter if characteristic parameter only has one merges, and can be separately that color development shows with the scale, improves visual; Attenuating with evaluation lithology granularity is example; Evaluating has six kinds; Wherein four kinds of information diminishes with granularity and increases, and has only two kinds of information to diminish with granularity and reduces, and focuses on according to information and merges principle; Need be with these the two kinds information translation that diminish with granularity and reduce for diminishing and increase with granularity, then six kinds of parameters become to have with lithology and attenuate and the focus information that increases.Merging width calculates with color value:

$\mathrm{LV}=\sqrt[2]{R^2+G^2+B^2}$

$\mathrm{CLV}=\sqrt[2]{3(R*G*B)}$

An information fusion visualization object can have 3-4 information, and three kinds of colors, a kind of color width are promptly arranged; If characteristic parameter is many; Adopt a plurality of information fusion objects; Can adopt multistage information fusion method, as: (R (V1)+G (V2)+B (V3)) → LV (V1, V2, V3), CLV (V1, V2, V3), (R (V4)+G (V5)+B (V6)) → LV (V4, V5, V6), CLV (V4, V5, V6);

R(LV(V4、V5、V6))+G(LV(V4、V5、V6))+B(V7)→LV(LV(V4、V5、V6)、LV(V4、V5、V6)、V7)、CLV(LV(V4、V5、V6)、LV(V4、V5、V6)、V7)。

According to focusing on planning and design; The characteristic parameter that volcanics is bored in the record log data merges scale meritization, is converted into RGB color value (0-255), and the volcanics rock signature parametric line value of setting scale meritization is that (characteristic parameter is the scope of a measured value to VL; Show that boring in the record well logging is exactly the curve values scope); Volcanics rock signature parameter minimum value is VMIN, and volcanics rock signature parameter maximal value VMAX is set at R, G, B curve respectively according to curvilinear characteristic; Article one, curve is through after the focus criteriaization; Promptly change a scope into and be 0～255 curve, for the needs of information fusion can be set at the RGB three primary colors through assignment, concrete scale computing formula is:

When volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing when being the linear graduation standardized curve through scale:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{VL}-\mathrm{VMIN}}{\mathrm{VMAX}-\mathrm{VMIN}},$ Value after the planning increases with measured value, in information fusion, directly these values is shown with RGB;

Negative correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{VL}-\mathrm{VMIN}}{\mathrm{VMIN}-\mathrm{VMAX}},$ Value after the planning increases with measured value and reduces, and in information fusion, directly these values is shown with RGB;

When being converted into the standardized curve with identical qualitative sensing through scale, volcanics rock signature parametric line (characteristic parameter curve negotiating logarithmic scale is realized focus criteriaization) when being the logarithmic scale standardized curve:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{Ln}\left(\mathrm{VL}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)}{\mathrm{Ln}\left(\mathrm{VMAX}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)},$

Inverse correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{Ln}\left(\mathrm{VL}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)}{\mathrm{Ln}\left(\mathrm{VMIN}\right)-\mathrm{Ln}\left(\mathrm{VMAX}\right)},$

When being converted into the standardized curve with identical qualitative sensing through scale, volcanics rock signature parametric line (characteristic parameter curve negotiating statistical probability halving method is realized focus criteriaization) when being probability statistics scale merit curve:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{P\left(\mathrm{VL}\right)}{P\left(\mathrm{VMAX}\right)-P\left(\mathrm{VMIN}\right)},$

Inverse correlation planning $V\left(\mathrm{RGB}\right)=255\frac{P\left(\mathrm{VL}\right)}{P\left(\mathrm{VMIN}\right)-P\left(\mathrm{VMAX}\right)},$

P (VL) is a volcanics rock signature parameter cumulative probability;

P (VMIN) is volcanics rock signature parametric statistics minimum value place's cumulative probability (0);

P (VMAX) is volcanics rock signature parametric statistics maximal value place's cumulative probability (100).

Step 1032; Calculate the rgb space eigenwert according to the RGB color value; Length that said space characteristics value is the rgb space vector and RGB solid space volume are neglected the cube eigenwert greatly; As shown in Figure 7, the RGB of a measurement point merges can form a RGB body, and body characteristics just has the length of vector and RGB solid space volume to neglect the cube eigenwert greatly after calculating.Said RGB color value calculates the rgb space eigenwert and can merge and the corresponding relation that merges spatial parameter figure with reference to figure 9 alteration volcanics lithology RGB.

In this step, scale is merged standardized rgb value carry out the reconstruct of space characteristics value, calculate the rgb space eigenwert, the space characteristics value is divided into: the big small cubes eigenwert of length of rgb space vector (LV) and RGB solid space volume (CLV).Computing formula is:

$\mathrm{LV}=\sqrt[2]{R^2+G^2+B^2}$

$\mathrm{CLV}=\sqrt[2]{3(R*G*B)}$

In order to improve the different effects of record log data in information fusion of boring; Can adopt experience weights method, degneracy method, artificial weights method, calculate the rgb space eigenwert apart from weights method etc.; As select R color value weight to be (wB) for (WG), B color value weight for (WR), G color value weight, then length of rgb space vector (LV) and RGB solid space volume are neglected cube eigenwert (CLV) computing formula greatly and are:

$\mathrm{LV}=\sqrt[2]{{(\mathrm{WR}*R)}^2+{(\mathrm{WG}*G)}^2+{(\mathrm{WB}*B)}^2}$

$\mathrm{CLV}=\sqrt[2]{3(\mathrm{WR}*\mathrm{WG}*\mathrm{WB}*R*G*B)}$

Step 1033; Described RGB color value is fused into the color on the depth-logger; Said depth-logger is exactly the distance of local drilling platform square kelly of well-drilling borehole, by the recording mode decision of measurement parameter, sets the width that the corresponding degree of depth merges Show Color according to the rgb space eigenwert of correspondence again; Can obtain the fusion visualization result, just the characteristic model of volcanics lithology.

In this step; The RGB color value is fused into the chromatogram on the depth-logger; Select the space characteristics of RGB to merge the width demonstration again; Provide the synoptic diagram that fusion visualization result such as Fig. 6 have shown the characteristic model of volcanics lithology, wherein the lithology curve has comprised hole diameter (CAL) characteristic parameter curve, spontaneous potential (SP) characteristic parameter curve, natural gamma (GR) characteristic parameter curve respectively; The rerum natura curve comprises that respectively compensated neutron (CNL) characteristic parameter curve, lithology and density logging (DEN) characteristic parameter curve, rerum natura sensitivity curve mainly contain interval transit time (AC) characteristic parameter curve; Resistivity curve (because the accompanying drawing area is limit and can only be demonstrated resistivity) comprises invaded zone resistivity (RI) characteristic parameter curve respectively, electrically sensitivity curve mainly contains formation resistivity (RT) characteristic parameter curve, flushed zone resistivity (RXO) characteristic parameter curve.

In information fusion, if the lvalue of certain characteristic parameter is little, r value greatly then is positive correlation planning; R value is little, and lvalue greatly then is negative correlation planning, for example; The lvalue that lithology merges CAL in the chromatogram (LC) is 15, and r value is that 8 this characteristic parameter CAL are negative correlation planning, and the lvalue that merges CNL in the chromatogram (PC) in rerum natura is 0; R value is 50, and then for this characteristic parameter CNL is positive correlation planning, the lvalue that perhaps electrically merges RT in the chromatogram (RC) is 0; R value is 1000, and then this characteristic parameter RT is the positive correlation rule; In well logging fusion chromatogram (TLC), merge above-mentioned lithology and merged chromatogram, rerum natura fusion chromatogram and electrically merge chromatogram, also just be equivalent to merge simultaneously 9 characteristic parameter curves.

FMI micro-resistivity imaging figure, it changes the variation that has shown the microresistivity parameter with colourity; The alteration features curve has comprised compensated neutron (CNL) logging character parametric line, compressional wave time difference (DTCO) logging character parametric line, the drilling time log characteristic parameter curve that bores in the record well logging process; Fusion chromatogram based on rock element (ECS) has comprised DWTI, two kinds of characteristic parameter curves of DWFD_WALK2; The component index has comprised SiO ₂Weight percent content characteristic parameter curve, content (DWSI) the characteristic parameter curve of elemental silicon, natural gamma (GR) characteristic parameter curve; The alkalescence index has comprised weight percent content characteristic parameter curve, the K of CaO ₂The weight percent content characteristic parameter curve of O, Na ₂The weight percent content characteristic parameter curve of O; The ECS mineral comprise weight percent content, mud value content (WCLA), the long English matter mineral content (WQFM) of fosfosiderite (WPYR); Comprise the weight percent content of pyrite (WPYR), the weight percent content of siderite (WSID) in the color.Well logging has provided geologic lithology well logging result.

Fusion visualization result's color depends on the relative size of RGB; Bigger chromatogram value determines main color; Show that according to RGB mixed chromatogram characteristic space characteristics can be represented the space size after RGB focuses on, and reflects the strong and weak or big or small of corresponding volcanics characteristic parameter.

Step 104 is obtained the parameter of volcanics to be measured in boring the record well logging.Treat the parasitic volcano rock and detect, obtain the measurement parameter of this volcanics through physics and/or chemical means.

Step 105, with the measurement parameter of said volcanics to be measured form with said information fusion in the identical combination of characteristic parameter, mate with above-mentioned characteristic model.

Step 106 if mate successfully, is then exported this volcanics lithology to be measured, and for example the title of lithology can also be exported this volcanics geology is bored the relevant parameter that the record well logging waits operation, perhaps can also export other characteristic of this volcanics.

If comprised whether this volcanics is the alteration volcanics in the volcanics title of output; Then can be according to carrying out relevant work to the parameter of this alteration volcanics operation, for example to be reflected in the drilling well be the drillability significant change in the lithology alteration, improves like drillability after the identical lithology alteration; Reduce during brill; Be reflected on the well logging, landwaste argillization, color are fresh inadequately, alteration secondary mineral appearance etc., and the alteration that is reflected in the well logging changes; Significantly increase like the neutron well logging value, interval transit time increases, resistivity significantly descends, hole diameter enlarges or curve toothization etc.

Be illustrated in figure 8 as the structural representation of a kind of alteration volcanics of embodiment of the invention lithology recognition device.

Comprise: associative cell 801, characteristic parameter extraction unit 802, information fusion unit 803, measuring unit 804, matching unit 805, output unit 806;

Said associative cell 801 is used to set up the volcanics lithology and records the related of log data with corresponding brill;

Said characteristic parameter extraction unit 802 is used for extracting characteristic parameter in the brill record log data related with said volcanics lithology;

Said information fusion unit 803 is used for the characteristic parameter of said extraction is carried out information fusion, obtains the characteristic model of volcanics lithology;

Said measuring unit 804 is used for obtaining volcanics to be measured at the measurement parameter that bores the record well logging;

Said matching unit 805 is used for the measurement parameter of said volcanics to be measured is formed and the identical combination of said information fusion characteristic parameter, matees with above-mentioned characteristic model;

Said output unit 806 is used for exporting the volcanics lithological information corresponding with said volcanics to be measured when mating successfully.

As the further embodiment of the present invention, said information fusion unit 803 also comprises,

Standardized module 8031, rgb space characteristic value calculating module 8032, MBM 8033;

Said standardized module 8031; Be used for said characteristic parameter generating feature parametric line; Volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing through scale; And give corresponding RGB color value with said standardized curve each point, carry out the processing of carrying out like above-mentioned step 1031.

Said rgb space characteristic value calculating module 8032; Be used for calculating the rgb space eigenwert according to the RGB color value; Length that said space characteristics value is the rgb space vector and RGB solid space volume are neglected the cube eigenwert greatly, carry out the processing of carrying out like above-mentioned step 1032.

Said MBM 8033; Be used for described RGB color value is fused into the chromatogram on the depth-logger; Set RGB according to the rgb space eigenwert of correspondence again and merge the width that shows, obtain the characteristic model of said volcanics lithology, carry out the processing of carrying out like above-mentioned step 1033.

Through said apparatus to volcanics lithology identification have intuitively, accurately, characteristic rapidly and efficiently; Particularly the understanding to the alteration volcanics obtains to significantly improve; With drilling and coring delivery, the contrast of sidewall sampling lithology qualification result, alteration volcanics lithology recognition accuracy reaches more than 93%.

Above-described embodiment; The object of the invention, technical scheme and beneficial effect have been carried out further explain, and institute it should be understood that the above is merely embodiment of the present invention; And be not used in qualification protection scope of the present invention; All within spirit of the present invention and principle, any modification of being made, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (6)

1. alteration Lithology Identification Methods for Volcanic Rocks is characterized in that comprising:

In boring record well logging process, also comprise the volcanics rock core is carried out analysis of chemical elements, and set up the related of volcanics lithology and element chemical analysis data;

In the brill record log data related, extract characteristic parameter with said volcanics lithology;

The characteristic parameter of said extraction is carried out information fusion; Comprise in the characteristic model of acquisition volcanics lithology: with said characteristic parameter generating feature parametric line; Volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing through scale, and gives corresponding RGB color value said standardized curve each point; Calculate the rgb space eigenwert according to the RGB color value, length that said space characteristics value is the rgb space vector and RGB solid space volume are neglected the cube eigenwert greatly; Described RGB color value is fused into the chromatogram on the depth-logger; Set RGB according to the rgb space eigenwert of correspondence again and merge the width that shows; Obtain the characteristic model of said volcanics lithology, set up the mapping of boring record logging operation parameter with said characteristic model accordingly;

In addition, obtain in the measurement parameter of volcanics to be measured in boring the record well logging, treat the survey volcanics and detect, obtain the lithologic parameter of this volcanics through physics and/or chemical means;

With the measurement parameter of said volcanics to be measured form with said information fusion in the identical combination of characteristic parameter, mate with above-mentioned characteristic model;

If mate successfully, then the output volcanics lithology corresponding with said volcanics to be measured also exported the corresponding said brill record logging operation parameter of this volcanics to be measured.

2. method according to claim 1 is characterized in that, when volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing when being the linear graduation standardized curve through scale:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{VL}-\mathrm{VMIN}}{\mathrm{VMAX}-\mathrm{VMIN}},$

Inverse correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{VL}-\mathrm{VMIN}}{\mathrm{VMIN}-\mathrm{VMAX}},$

When volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing when being the logarithmic scale standardized curve through scale:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{Ln}\left(\mathrm{VL}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)}{\mathrm{Ln}\left(\mathrm{VMAX}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)},$

Inverse correlation planning $V\left(\mathrm{RGB}\right)=255\frac{\mathrm{Ln}\left(\mathrm{VL}\right)-\mathrm{Ln}\left(\mathrm{VMIN}\right)}{\mathrm{Ln}\left(\mathrm{VMIN}\right)-\mathrm{Ln}\left(\mathrm{VMAX}\right)},$

When volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing when being probability statistics scale merit curve through scale:

Positive correlation planning $V\left(\mathrm{RGB}\right)=255\frac{P\left(\mathrm{VL}\right)}{P\left(\mathrm{VMAX}\right)-P\left(\mathrm{VMIN}\right)},$

Inverse correlation planning $V\left(\mathrm{RGB}\right)=255\frac{P\left(\mathrm{VL}\right)}{P\left(\mathrm{VMIN}\right)-P\left(\mathrm{VMAX}\right)},$

The volcanics rock signature parametric line value of above-mentioned setting scale meritization is VL; Volcanics rock signature parameter minimum value is VMIN; Volcanics rock signature parameter maximal value VMAX; P (VL) is a volcanics rock signature parameter cumulative probability, and P (VMIN) is a volcanics rock signature parametric statistics minimum value place cumulative probability, and P (VMAX) is a volcanics rock signature parametric statistics maximal value place cumulative probability.

3. method according to claim 2 is characterized in that, calculates the rgb space eigenwert and is specially:

$\mathrm{LV}=\sqrt[2]{R^2+G^2+B^2}$

$\mathrm{CLV}=\sqrt[2]{3(R*G*B)}$

Wherein LV is the length of rgb space vector, and CLV is that RGB solid space volume is neglected the cube eigenwert greatly.

4. method according to claim 2; It is characterized in that; Described RGB color value is being fused into the chromatogram on the depth-logger; Set RGB according to the rgb space eigenwert of correspondence again and merge the width that shows, the characteristic model that obtains said volcanics lithology also comprises before, adopts multistage information fusion method that a plurality of RGB color values and a plurality of rgb space eigenwert are merged.

5. alteration volcanics lithology recognition device is characterized in that comprising:

Associative cell, characteristic parameter extraction unit, information fusion unit, measuring unit, matching unit, output unit;

Said associative cell is used to set up the volcanics lithology and records the related of log data with corresponding brill;

Said characteristic parameter extraction unit is used for extracting characteristic parameter in the brill record log data related with said volcanics lithology;

Said information fusion unit is used for the characteristic parameter of said extraction is carried out information fusion, obtains the characteristic model of volcanics lithology;

Said measuring unit is used for obtaining volcanics to be measured at the measurement parameter that bores the record well logging;

Said matching unit is used for the measurement parameter of said volcanics to be measured is formed and the identical combination of said information fusion characteristic parameter, matees with above-mentioned characteristic model;

Said output unit is used for exporting the volcanic rock lithological information corresponding with said volcanic rock to be measured when the match is successful.

6. device according to claim 5 is characterized in that, said information fusion unit also comprises,

Standardized module, rgb space characteristic value calculating module, MBM;

Said standardized module; Be used for said characteristic parameter generating feature parametric line; Volcanics rock signature parametric line is converted into the standardized curve with identical qualitative sensing through scale, and gives corresponding RGB color value said standardized curve each point;

Said rgb space characteristic value calculating module is used for calculating the rgb space eigenwert according to the RGB color value, and length that said space characteristics value is the rgb space vector and RGB solid space volume are neglected the cube eigenwert greatly;

Said MBM is used for described RGB color value is fused into the chromatogram on the depth-logger, sets RGB according to the rgb space eigenwert of correspondence again and merges the width that shows, obtains the characteristic model of said volcanics lithology.

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