CN111323844A - Lithology identification method and system of complex gravel rock mass based on curve reconstruction - Google Patents
Lithology identification method and system of complex gravel rock mass based on curve reconstruction Download PDFInfo
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Abstract
The invention relates to a lithology identification method and a lithology identification system of a complex gravel rock mass based on curve reconstruction, wherein the method comprises the following steps: determining key lithology of the complex gravel rock mass; determining a logging response value of key lithology through a cross plot method; according to the logging response value of key lithology, constructing a characteristic curve K by using deep lateral resistivity and a natural gamma logging response value, and constructing a characteristic curve F by using a sound wave time difference and a compensated neutron logging response value; and carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F. The method comprises the steps of firstly utilizing core observation and logging information to determine key lithology, selecting natural gamma and resistivity sensitive to reservoir lithology, compensating neutron and acoustic wave time difference curves, carrying out curve reconstruction to amplify response values of logging curves, and finally compiling a reconstructed curve intersection graph to finish quantitative identification of lithology of complex gravel rock masses, so that reliable guidance is provided for subsequent exploration and development of a research area, and the method is expected to provide a basis for basic geological theory research and development.
Description
Technical Field
The invention relates to the technical field of oil field development, in particular to a lithology identification method and system of a complex gravel rock mass based on curve reconstruction.
Background
The complex gravel rock mass is usually the result of the rapid mixing and stacking of near sources and is characterized by complex lithology, poor separation and high argillaceous content, which leads to higher difficulty in lithology quantitative identification.
At present, the lithology qualitative identification method mainly comprises a support vector machine method, an FMI (Formation micro resistivity scanning imaging) lithology identification method and a conventional logging curve cross-plot method. Lithology recognition is carried out by utilizing a conventional logging curve, conglomerates, gray matter conglomerates and oil layers have high resistance characteristics, the resistivity characteristics of the oil layers and the resistivity characteristics of the conglomerates are greatly overlapped, and quantitative recognition difficulty of most curves is high. Therefore, in order to accurately and quantitatively identify the lithology of the complex gravel rock mass, a new discrimination method needs to be established.
Disclosure of Invention
The invention provides a method and a system for identifying lithology of a complex gravel rock mass based on curve reconstruction aiming at the technical problems in the prior art, and solves the problem that lithology of the complex gravel rock mass cannot be accurately and quantitatively identified in the prior art.
The technical scheme for solving the technical problems is as follows: a lithology identification method of a complex gravel rock mass based on curve reconstruction comprises the following steps:
step 1, determining key lithology of the complex gravel rock mass;
step 2, determining the logging response value of the key lithology through a cross plot method;
step 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value;
and 4, carrying out quantitative identification on the key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
A lithology identification system of a complex gravel rock mass based on curve reconstruction comprises: the device comprises a key lithology determining module, a key lithology logging response value determining module, a curve reconstructing module and a lithology identifying module;
the key lithology determining module is used for determining the key lithology of the complex gravel rock mass;
the key lithology logging response value determining module is used for determining the key lithology logging response value through a cross plot method;
the curve reconstruction module is used for constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value according to the logging response value of the key lithology, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value;
and the lithology identification module is used for carrying out quantitative identification on the key lithology according to the value ranges of the characteristic curve K and the characteristic curve F. .
The invention has the beneficial effects that: the invention provides a lithology recognition method and a lithology recognition system of a complex gravel rock mass based on curve reconstruction, which are characterized in that on the basis of investigation of a large amount of documents, core observation and logging information are firstly utilized to determine key lithology, natural Gamma (GR) sensitive to reservoir lithology, true formation Resistivity (RT), Compensated Neutron (CNL) and Acoustic time difference (AC) curves are selected for curve reconstruction, response values of logging curves are amplified, and finally a reconstructed curve cross-plot is compiled to complete quantitative recognition of the lithology of the complex gravel rock mass, provide reliable guidance for subsequent exploration in a research area and provide basis for research and development of basic geological theory. A set of complex gravel rock lithology identification chart suitable for a research area is established, various lithology quantitative interpretation standards are established, and practical verification shows that the method and the system can divide reservoir lithology quantitatively and provide reliable lithology data for subsequent exploration and development of the research area.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the method for determining the key lithology of the complex gravel rock body in the step 1 comprises core observation and/or logging information.
Further, before determining the log response value of the key lithology through the cross-plot method in the step 2, the method further includes:
and (5) adopting a standard layer trend method to carry out well logging curve standardization.
Further, the key lithology determined in step 1 includes: coarse sandstone, mudstone, siltstone, medium-fine sandstone, conglomerate, fine conglomerate and medium-fine sandstone in gray matter.
Further, the step 2 further comprises: determining the lithology of the mudstone, the siltstone and the medium and fine sandstone through the resistivity, the acoustic time difference and the neutron porosity:
when RT is less than 4.75 omega.m, the lithology is mudstone; when 4.75 omega-m < RT <9 omega-m, the lithology is siltstone or medium-fine sandstone; when RT is more than 9 omega.m, lithology is glutenite, glutenite and fine sandstone in gray matter; when AC is less than 202.9 μ s/m and CNL is less than 15%, the gray matter interlayer is corresponded;
where RT represents resistivity, AC represents acoustic time difference, and CNL represents compensation neutrons.
Further, the equations of the characteristic curve K and the characteristic curve F in step 3 are respectively:
K＝RT'/GR'；
F＝log(AC'×CNL')；
wherein RT 'is the normalized value of the deep lateral resistivity logging curve, GR' is the normalized value of the natural gamma logging curve, AC 'is the normalized value of the acoustic time difference logging curve, and CNL' is the normalized value of the compensated neutron logging curve.
Further, in the step 4, the complex lithology F-K cross plate is manufactured to determine that the boundary of different lithologies is as follows:
mudstone: f3.8, 4.2 and K0, 0.06; siltstone: f3.7, 4.0 and K0.06, 0.08; medium and fine sandstone: f3.6, 3.9 and K0.08, 0.13; conglomerate: f3.6, 3.8 and K0.13, 0.22; fine conglomerate: f3.3, 3.7 and K0.12, 0.24; gray medium fine sandstone: f3.3, 3.6 and K0.24, 0.38.
The beneficial effect of adopting the further scheme is that: determining key lithology by taking core observation as a standard, and ensuring reliability; the well log data is normalized to overcome and eliminate systematic errors caused by different instruments or modes of operation.
Drawings
FIG. 1 is a flow chart of a lithology identification method of a complex gravel rock mass based on curve reconstruction provided by the invention;
FIG. 2 is a schematic view of the north 16 well region structure according to an embodiment of the present invention;
FIG. 3(a) is a natural gamma distribution diagram for the north 16 well according to an embodiment of the present invention;
FIG. 3(b) is a sound time difference distribution diagram of the north 16 well zone according to the embodiment of the present invention;
FIG. 3(c) is a neutron porosity profile for a north 16 well region provided by an embodiment of the present invention;
FIG. 3(d) is a resistivity profile of a north 16 well region provided in accordance with an embodiment of the present invention;
FIG. 4 is a cross-plot of resistivity and neutron provided by an embodiment of the present invention;
FIG. 5 is a chart of the acoustic moveout versus neutron interaction provided by an embodiment of the present invention;
FIG. 6 is a cross plot of resistance versus acoustic time difference provided by an embodiment of the present invention;
FIG. 7 is a cross-plot of resistivity versus natural gamma according to an embodiment of the present invention;
FIG. 8 is a F-K rendezvous block diagram in accordance with an embodiment of the present invention;
FIG. 9 is a structural block diagram of an embodiment of a lithology identification system for complex gravel rock mass based on curve reconstruction provided by the invention;
fig. 10 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
101. the device comprises a key lithology determination module 102, a key lithology logging response value determination module 103, a curve reconstruction module 104, a lithology identification module 201, a processor 202, a communication interface 203, a memory 204 and a communication bus.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a flow chart of a lithology identification method of a complex gravel rock mass based on curve reconstruction, and as can be seen from fig. 1, the method includes:
step 1, determining key lithology of a complex gravel rock body.
And 2, determining a logging response value of the key lithology through a cross plot method.
And 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value.
And 4, carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
The invention provides a lithology identification method and a lithology identification system of a complex gravel rock mass based on curve reconstruction, which are characterized in that on the basis of investigation of a large amount of documents, core observation and logging information are firstly utilized to determine key lithology, natural Gamma (GR), Resistivity (RT), Compensation Neutron (CNL) and sound wave time difference (AC) curves sensitive to reservoir lithology are selected to carry out curve reconstruction, response values of the logging curves are amplified, and finally a reconstructed curve intersection graph is compiled to complete quantitative identification of the lithology of the complex gravel rock mass, so that reliable guidance is provided for subsequent exploration and development of a research area, and the method and the system are expected to provide bases for basic geological theory research and development. A set of complex gravel rock lithology identification chart suitable for a research area is established, various lithology quantitative interpretation standards are established, and practical verification shows that the method and the system can divide reservoir lithology quantitatively and provide reliable lithology data for subsequent exploration and development of the research area.
Example 1
The embodiment 1 provided by the invention is an embodiment of a lithology identification method of a complex gravel rock mass based on curve reconstruction, and the embodiment of the method comprises the following steps:
step 1, determining key lithology of a complex gravel rock body;
further, methods of determining key lithology of complex gravel rock masses include core observation and/or logging data.
The determination of key lithology is based primarily on the following two aspects: directly observing the consciousness rock core; the second is logging data. The reliability of rock property identification by using core observation is higher than that of logging information, so that when the rock property observed by the core is contradictory to the logging rock property, the rock property observed by the core is taken as the standard.
In particular, key lithologies may include: coarse sandstone, mudstone, siltstone, medium-fine sandstone, conglomerate, fine conglomerate and medium-fine sandstone in gray matter.
And 2, determining a logging response value of the key lithology through a cross plot method.
For oil fields, it is difficult to ensure that all the well logs are on the same type of instrument, on a uniform standard scale and in the same mode of operation during long-term exploration and development. This will inevitably lead to errors based on the well-to-well scaling factor. Therefore, there is a need to normalize the log data to overcome and eliminate such system errors. Therefore, before determining the logging response value of the key lithology through the cross-plot method in the step 2, the method further comprises the following steps:
and (5) adopting a standard layer trend method to carry out well logging curve standardization.
The step 2 further comprises the following steps: determining the lithology of the mudstone, the siltstone and the medium and fine sandstone through the resistivity, the acoustic time difference and the neutron porosity:
when RT is less than 4.75 omega.m, the lithology is mudstone; when 4.75 omega-m < RT <9 omega-m, the lithology is siltstone or medium-fine sandstone; when RT is more than 9 omega.m, lithology is glutenite, glutenite and fine sandstone in gray matter; when AC <202.9 μ s/m and CNL < 15%, it corresponds to gray matter interlayer.
Where RT represents resistivity, AC represents acoustic time difference, and CNL represents compensation neutrons.
And 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value.
In step 3, the equations of the characteristic curve K and the characteristic curve F are respectively as follows:
K＝RT'/GR'；
F＝log(AC'×CNL')；
wherein RT 'is the normalized value of the deep lateral resistivity logging curve, GR' is the normalized value of the natural gamma logging curve, AC 'is the normalized value of the acoustic time difference logging curve, and CNL' is the normalized value of the compensated neutron logging curve.
Mud rock, siltstone and medium and fine sandstone can be effectively determined through resistivity, acoustic time difference and neutron porosity, and are difficult to divide for other lithologies. According to the cross plot of the logging curves, the coarser the granularity is, the larger the resistance value is, and the smaller the difference value between the neutron porosity and the sound wave is for mudstone, siltstone, medium-fine sandstone, fine conglomerate and glutenite. Generally speaking, for sandstone oil reservoirs, natural gamma values can effectively distinguish lithology, and for complex lithology oil reservoirs with fast mixed accumulation of sources, the complex lithology oil reservoirs are difficult to distinguish due to high content of heterogeneous bases. Based on the understanding, a characteristic curve K is constructed by using the deep resistivity and the natural gamma logging response value, and a characteristic curve F is constructed by using the acoustic time difference and the compensated neutron logging response value to amplify the lithological logging response characteristic and try to judge the complex sandstone.
And 4, carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
In the step 4, the complex lithology F-K intersection plate is manufactured to determine that the boundary of different lithologies is as follows:
mudstone: f3.8, 4.2 and K0, 0.06; siltstone: f3.7, 4.0 and K0.06, 0.08; medium and fine sandstone: f3.6, 3.9 and K0.08, 0.13; conglomerate: f3.6, 3.8 and K0.13, 0.22; fine conglomerate: f3.3, 3.7 and K0.12, 0.24; gray medium fine sandstone: f3.3, 3.6 and K0.24, 0.38.
Example 2
Embodiment 2 provided by the invention is a specific application embodiment of the lithology identification method of the complex gravel rock mass based on curve reconstruction provided by the invention, taking the north 16-well broken nose in the south of the northeast raised strip and the west of the three north raised northwest of the southeast of the pseudo-sonnery basin as an example, as shown in fig. 2, a structural position schematic diagram of the north 16-well area provided by the embodiment of the invention is provided, and the northwest raised strip is a positive secondary structural unit in the direction close to the north and south. The North 16 well region is a nose bump, severed by the three North faults at the North edge of the three North bumps, and complicated by many small faults. The developed oil layer of the phoenix tree ditch group in the north 16 well area is a alluvial fan-fan delta. Substantially at P3wt1 4Late or terminal coverage by west invaded lake water begins to emerge as delta, by the end of P3wt12, the end of delta history enters the sedimentation phase of the lake delta. The phoenix tree ditch group is a set of overburden, P3wt1 4The deposition range is limited to the north, P3wt1 3Over-extending to the south until three fractures break north and west and east, P3wt1 2Has been extended to be in the south of three fractures. The three projections south and north provide the source of the matter when the phoenix ditch group is deposited.
Step 1, determining key lithology of a complex gravel rock body.
Through analyzing and researching the core sample of the area, the rock types of the 16 well areas in the north of the double-system phoenix tree ditch group are found to be complex, and the types of fine conglomerate, glutenite, medium and fine sandstone, siltstone, mudstone, coarse sandstone and the like can be seen:
(1) the breccite and the glutenite are mainly gray and grey white, the particle size range is 0.5-10 mm, the sorting is poor-medium, and the cobsonite and the glutenite are rounded and have a shape of a semicircle or a corner. In the fandelta underwater diversion river channel and the diversion beach in the research area, the bottom scouring phenomenon of the glutenite is common.
(2) The medium and fine sandstones are mainly grey, grey green fine sandstones and siltstones, the grain sizes of the medium and fine sandstones are found from 0.125-0.5 mm, the sorting is medium-poor, the clastic particles are in a shape of a sub-circle-corner, the bedding development in the sandstones is mostly seen in underwater diversion riverways, estuary dams and diversion beaches of research areas, and the common types are as follows: parallel, staggered and blocky.
(3) The mudstone color in the research area has gray, dark gray, gray black and other hues, wherein the delta subphase develops gray, dark gray mudstone, silty mudstone, mudstone with the visible reduced hue in the subphase of the shores lake, and the mudstone in the subphase of the semi-deep lake mostly appears thick-layer output, and the color is mostly dark gray and gray black.
In summary, the area is an underwater deposition environment, the development of gray, gray and gray colored glutenite and glutenite shows that the deposition environment is close to the source, and the deposition environment of the oil reservoir is a fan delta in combination with the research results of the predecessors. The research area shares 6 wells of the coring well, and is finally divided into 7 main lithologies according to the similarity between lithologic characteristics and a deposition environment on the basis of core observation description and various sign researches, and the lithology classification of the north 16 wells provided by the embodiment of the invention is shown in table 1.
TABLE 1 lithology Classification of North 16 well regions
And 2, determining a logging response value of the key lithology through a cross plot method.
Three oil fields in the north have been developed since the last 80 years, and the logging work is completed by various instruments in nearly 40 years. For oil fields, it is difficult to ensure that all the well logs are on the same type of instrument, on a uniform standard scale and in the same mode of operation during long-term exploration and development. This will inevitably lead to errors based on the well-to-well scaling factor. Therefore, there is a need to normalize the log data to overcome and eliminate such system errors. According to the actual condition of a research work area, a standard layer trend method is adopted to carry out well logging curve standardization, a top mudstone section of a first section of two oil groups and a first sand group is selected as a standard layer, the sound wave time difference, natural gamma, resistivity and neutron density value of the section of mudstone are stable, the value of the section of mudstone is extracted to be used as a histogram, as shown in figures 3(a) - (d), the natural gamma distribution diagram, the sound wave time difference distribution diagram, the neutron porosity distribution diagram and the resistivity distribution diagram of the north 16 well area provided by the embodiment of the invention are respectively, the well logging curve is standardized according to the distribution rule of well logging curve values, and lithology explanation is carried out on the well logging curve on the basis.
On the basis of fully utilizing 2 types of data of core observation and logging of a 6-opening coring well of a north 16 well zone, the lithology is restored by combining logging data, and as shown in figures 4-7, lithology interpretation conclusion which can be implemented in a research area is obtained by respectively providing resistivity and neutron, acoustic wave time difference and neutron, resistance and acoustic wave time difference and resistivity and natural gamma intersection charts for the embodiment of the invention:
(1) when RT is less than 4.75 omega.m, the lithology is basically mudstone; when 4.75 omega-m < RT <9 omega-m, the lithology is siltstone or medium-fine sandstone; when RT is greater than 9 omega.m, the lithology is conglomerate, tergite and fine sandstone in gray matter.
(2) When AC is less than 202.9 mu s/m and CNL is less than 15%, the well logging curve has obvious gray matter tips, which correspond to gray matter interlayer.
And 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value.
And 4, carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
And (3) reconstructing the logging curve, drawing an intersection graph, completing quantitative identification of complex lithology in the research area, and finally quantitatively identifying 6 lithologies such as mudstone, siltstone, medium and fine sandstone, glutenite, breccite and the like. FIG. 8 shows an F-K rendezvous block diagram according to an embodiment of the invention.
The lithology of the phoenix tree ditch group in the research area is complex, only mudstone, siltstone and fine sandstone in the gray matter can be determined through a conventional logging curve chart, and the lithology of a complex gravel rock body can be effectively distinguished by adopting an F-K intersection chart. The lithology judgment result is better matched with the well logging curve and the coring lithology, and the accuracy is more than 80%. Therefore, the lithology recognition chart can be used as a standard for lithology recognition of the phoenix trench group in the north 16 well region, and meanwhile, a new idea is provided for complex lithology body recognition.
Example 3
Embodiment 3 provided by the present invention is an embodiment of a lithology identification system of a complex gravel rock mass based on curve reconstruction provided by the present invention, and as shown in fig. 9, is a structural block diagram of an embodiment of a lithology identification system of a complex gravel rock mass based on curve reconstruction provided by the present invention, as can be seen from fig. 9, the system includes: the device comprises a key lithology determination module 101, a key lithology logging response value determination module 102, a curve reconstruction module 103 and a lithology identification module 104.
And the key lithology determining module 101 is used for determining the key lithology of the complex gravel rock body.
And the key lithology logging response value determining module 102 is used for determining the key lithology logging response value through a cross-plot method.
And the curve reconstruction module 103 is used for constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value according to the logging response value of the key lithology.
And the lithology identification module 104 is used for carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
Fig. 10 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 10, the electronic device may include: the system comprises a processor 201, a communication interface 202, a memory 203 and a communication bus 204, wherein the processor 201, the communication interface 202 and the memory 203 are communicated with each other through the communication bus 204. The processor 201 may call a computer program stored on the memory 203 and operable on the processor 201 to execute the method for identifying lithology of complex gravel rock mass based on curve reconstruction provided by the above embodiments, for example, including: step 1, determining key lithology of a complex gravel rock body. And 2, determining a logging response value of the key lithology through a cross plot method. And 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value. And 4, carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
Embodiments of the present invention further provide a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to, when executed by a processor, perform the method for identifying lithology of a complex gravel rock mass based on curve reconstruction provided in the foregoing embodiments, for example, the method includes: step 1, determining key lithology of a complex gravel rock body. And 2, determining a logging response value of the key lithology through a cross plot method. And 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value. And 4, carrying out quantitative identification on key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A lithology identification method of a complex gravel rock body based on curve reconstruction is characterized by comprising the following steps:
step 1, determining key lithology of the complex gravel rock mass;
step 2, determining the logging response value of the key lithology through a cross plot method;
step 3, according to the logging response value of the key lithology, constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value;
and 4, carrying out quantitative identification on the key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
2. The method as claimed in claim 1, wherein the method of determining key lithology of the complex gravel rock mass in step 1 comprises core observation and/or logging data.
3. The method of claim 1, wherein determining the log response value for the key lithology in step 2 by cross-correlation further comprises:
and (5) adopting a standard layer trend method to carry out well logging curve standardization.
4. The method of claim 1, wherein the key lithology determined in step 1 comprises: coarse sandstone, mudstone, siltstone, medium-fine sandstone, conglomerate, fine conglomerate and medium-fine sandstone in gray matter.
5. The method according to claim 4, wherein the step 2 further comprises: determining the lithology of the mudstone, the siltstone and the medium and fine sandstone through the resistivity, the acoustic time difference and the neutron porosity:
when RT is less than 4.75 omega.m, the lithology is mudstone; when 4.75 omega-m < RT <9 omega-m, the lithology is siltstone or medium-fine sandstone; when RT is more than 9 omega.m, lithology is glutenite, glutenite and fine sandstone in gray matter; when AC is less than 202.9 μ s/m and CNL is less than 15%, the gray matter interlayer is corresponded;
where RT represents resistivity, AC represents acoustic time difference, and CNL represents compensation neutrons.
6. The method according to claim 1, wherein the equations of the characteristic curve K and the characteristic curve F in step 3 are respectively:
K＝RT'/GR'；
F＝log(AC'×CNL')；
wherein RT 'is the normalized value of the deep lateral resistivity logging curve, GR' is the normalized value of the natural gamma logging curve, AC 'is the normalized value of the acoustic time difference logging curve, and CNL' is the normalized value of the compensated neutron logging curve.
7. The method of claim 6, wherein the step 4 is performed by making a complex lithology F-K cross plate to determine the boundary of different lithologies as follows:
mudstone: f3.8, 4.2 and K0, 0.06; siltstone: f3.7, 4.0 and K0.06, 0.08; medium and fine sandstone: f3.6, 3.9 and K0.08, 0.13; conglomerate: f3.6, 3.8 and K0.13, 0.22; fine conglomerate: f3.3, 3.7 and K0.12, 0.24; gray medium fine sandstone: f3.3, 3.6 and K0.24, 0.38.
8. A lithology identification system for complex gravel rock mass based on curve reconstruction, the system comprising: the device comprises a key lithology determining module, a key lithology logging response value determining module, a curve reconstructing module and a lithology identifying module;
the key lithology determining module is used for determining the key lithology of the complex gravel rock mass;
the key lithology logging response value determining module is used for determining the key lithology logging response value through a cross plot method;
the curve reconstruction module is used for constructing a characteristic curve K by using the deep lateral resistivity and the natural gamma logging response value according to the logging response value of the key lithology, and constructing a characteristic curve F by using the acoustic time difference and the compensated neutron logging response value;
and the lithology identification module is used for carrying out quantitative identification on the key lithology according to the value ranges of the characteristic curve K and the characteristic curve F.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor when executing the program implements the steps of the method for identifying lithology of a complex gravel rock mass based on curve reconstruction according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for identifying lithology of a complex gravel rock mass based on curve reconstruction according to any one of claims 1 to 7.
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