CN109061763A - Carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation - Google Patents
Carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation Download PDFInfo
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Abstract
The invention discloses a kind of disconnected solution oil reservoir cave Comprehensive Log Evaluations of carbonate rock, its Comprehensive Evaluation of Well Logging main system control module is by calling the Reservoir types identification modules such as cave to realize the judgement of Reservoir type, cavern filling object genetic type identification module is called to realize the judgement of charges genetic type, it calls cavern filling species type discrimination module to realize the judgement of charges lithology type, cavern filling degree evaluation module is called to realize the calculating of cavern filling degree.The beneficial effects of the present invention are: studying sensitive well logging type from the logging response character of every kind of Reservoir type, summarizing judgment criteria, sensitive instruction parameter is proposed, and form software module, output Reservoir type indicative curve；Comprehensive for the comprehensive characterization content in cave, not only cavern filling object genetic type and lithology type including qualitative discrimination, but also the filling operation including semi-quantitative assessment can be realized the thoroughly evaluating in the disconnected solution oil reservoir cave of carbonate rock.
Description
Technical field
The present invention relates to petroleum exploration fields, specifically, it is comprehensive to be related to a kind of disconnected solution oil reservoir cave well logging of carbonate rock
Close evaluation method.
Background technique
1. prior art
The disconnected solution of carbonate rock is the new Oil Reservoir Types of one kind of discovered in recent years, is mainly formed by disconnected control corrosion.From spy
It is analyzed in sign, the disconnected solution oil-gas reservoir distribution mode multiplicity of carbonate rock has ribbon, sandwich 3 class of pie peace plate, preserves sky
Between complicated, Reservoir type multiplicity.Fracture hole reservoir space in carbonates mainly includes matrix pores (corrosion hole), crack, cave etc.,
Carbonate formation can be divided into the cave of large scale and the fracture and cave reservoir of small scale according to scale difference.According to preserving sky
Between configuration mode it is different, fracture-cavity type carbonate reservoir is divided into 5 classes on Reservoir type, is crack, hole, crack-hole
Hole, unfilled cave and filling cave.For filling cave, also there is significantly different, filling operation in the source of charges
Also there were significant differences again.
Current progress, generally be directed to the differentiation of cavern filling lithology type, used method is mainly handed over
The method of meeting figure.
2. the shortcomings that prior art
Identification and charges lithology typing interpretation of the current Comprehensive Assessment Technology major limitation in cave, the method for use is also only
It is analyzed only with intersection drawing method and its discrimination standard, is not explained from the origin cause of formation of charges, to filling journey
The understanding quantification degree of degree is not high.
Summary of the invention
The present invention is precisely in order to improve the precision of well log interpretation, for geophysics provides basic data with geological analysis and sets
A kind of disconnected solution oil reservoir cave Comprehensive Log Evaluation of carbonate rock of meter.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of disconnected solution oil reservoir cave Comprehensive Log Evaluation of carbonate rock, Comprehensive Evaluation of Well Logging main system control module pass through
It calls the Reservoir types identification modules such as cave to realize the judgement of Reservoir type, calls cavern filling object genetic type identification module real
The judgement of existing charges genetic type, calls cavern filling species type discrimination module to realize the judgement of charges lithology type, adjusts
The calculating of filling operation is realized with cavern filling degree evaluation module；It is comprised the concrete steps that:
The first step carries out the judgement of Reservoir type；Log data is inputted, according to deep lateral resistivity-natural gamma cross plot knot
It closes fracture porosity constraint and judges Reservoir type；Natural gamma GR, deep lateral resistivity RD, fracture porosity are inputted in the module
PORF curve exports disconnected Reservoir type and differentiates indicative curve CAVE_2, identifies cave according to curve of output feature；
Second step carries out the judgement of cavern filling object genetic type；Log data is inputted, shale content is calculated, is contained according to shale
The shallow lateral cross plot of amount-and its discrimination standard judge that charges genetic type is differentiated；Shallow lateral resistance is inputted in the module
Rate RS, density DEN, shale content SH and Reservoir type differentiate instruction CAVE_2 curve, Filler curve are exported, according to output
Curvilinear characteristic judges charges genetic type；
Third step carries out the judgement of cavern filling object lithology type；Log data is inputted, according to 6 kinds of cross plots and its differentiates mark
Standard judges charges lithology type；The shallow lateral resistivity RS of input, deep lateral resistivity RD, natural gamma GR, close in the module
DEN, interval transit time AC and neutron CNL are spent, packing curve is exported, charges lithology class is judged according to curve of output feature
Type；
4th step carries out the calculating of cavern filling degree；Log data is inputted, gamma relative amount is calculated, according to respective formula
Filling operation indicative curve is calculated, then filling operation comprehensive descision is obtained by the filling operation criteria for classifying；In filling operation meter
It calculates and inputs KTH, GR, CAVE_2 curve in module, export VUG1, VUG2 curve, inputted in filling operation type identification module
Curve VUG1, VUG2 curve, curve of output VUGt curve；According to a certain cave of filling operation indicative curve comprehensive descision of output
Overall filling operation.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and the differentiation that cave is exported in the first step refers to
Show realized on the basis of the discrimination standard by establishing different reservoir spaces；Fracture and cave reservoir reservoir space log response
Feature has differences with the difference of reservoir space type, passes through al-lateral resistivity, natural gamma, compensated neutron and sound wave
GR-RS and AC-CNL cross plot is established in time difference logging method；Wherein, in GR-RS cross plot cave deep lateral resistivity with from
There are notable differences for right gamma, and the sound wave in cave and neutron well logging also have difference with other Reservoir types in AC-CNL cross plot
It is different, the discrimination standard of different reservoir spaces is established using two cross plots.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, the Reservoir types identification module such as cave fortune
Cave differentiation and comprehensive analysis are carried out with RBF neural network algorithm；RBF is the three-layer forward networks with single hidden layer, first layer
For input layer, it is made of the log data sensitive to Reservoir type；The second layer is hidden layer, the transformation letter of neuron in hidden layer
Number i.e. radial basis function is the non-negative linearity function to central point radial symmetric and decaying, which is local acknowledgement's function, than
The originally function value of global response；Third layer is output layer, is responded to input data, is output reservoir class herein
The differentiation in the differentiation of type, especially cave.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and charges genetic type is sentenced in second step
Other establishment of standard method is: the charges of different origins have different logging response characters, wherein the depth bilaterally resistance
Rate, gamma ray log response are more sensitive, and there is also very big difference, shale contents to be asked by natural gamma for corresponding shale content
It takes, to construct the cross plot of cavern filling object different origins type；Cavern filling is constructed using Vsh and shallow lateral resistivity
Object genetic type identifies line of demarcation, and expression formula is respectively as follows:
。
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and charges lithology type is sentenced in third step
Other establishment of standard method is: different lithology charges have different logging response characters, according to shale, sand shale, chiltern,
The logging response character of 5 kinds of lithology charges of breccia and calcite, utilizes natural gamma GR, deep lateral resistivity RD, shallow side
To resistivity RS, interval transit time AC, neutron CNL and density DEN, combine two-by-two construct respectively 6 cave difference charges at
Because of type identification plate, to establish the criteria for interpretation of cavern filling object Lithology Discrimination.
The disconnected solution oil reservoir cave Comprehensive Log Evaluation of the carbonate rock will be studied according to filling operation in cave
Area cave is divided into unfilled, half filling and three kinds of situations of full-filling.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, the 4th step cavern filling degree evaluation mould
Block implementation steps:
Firstly, when using natural gamma GR, deep lateral resistivity RD, shallow lateral resistivity RS, neutron CNL, density DEN and sound wave
Poor AC is intersected two-by-two, establishes the interpretation chart of cave difference filling operation respectively；
Secondly, it is preferred that sensitive parameter of the natural gamma GR as reflection cave difference filling operation, and calculates cavern filling degree；
Define a parameter IVUG, referred to as natural gamma relative value carries out quantitatively characterizing to cavern filling degree:
(3)
In formula, X is gamma ray curve value, XminFor natural gamma limestone baseline value, XmaxThe gamma in cave is filled for pure shale
Maximum value；
Finally, establishing cavern filling degree interpretation chart and standard；Cavern filling degree is higher, IVUGValue increases, and utilizes the parameter
The interpretation chart of cavern filling degree can be obtained with shallow lateral resistivity, and establish the indicateing arm of cave difference filling operation
It is quasi-.
By to carbonate rock break solution oil reservoir cave comprehensive logging evaluation introduction, advantage are as follows: (1) evaluate content
It comprehensively, had not only included the evaluation of cavern filling degree, but also the evaluation including charges type, charges type had both included lithology type
Evaluation, and the identification including genetic type.(2) cavern filling object lithology class is directed in research method log response mechanism respectively
The needs of type, genetic type and filling operation evaluation, preferably sensitive log data, embody theoretical method foundation.(3)
RBF algorithm is introduced in Reservoir type and cave differentiate and fracture evaluation result carries out comprehensive identification, embodies method and technology
Advance.(4) it is directed to the above method, has write data processing module, is able to satisfy the needs of scale processing and application.
The beneficial effects of the present invention are: sensitive well logging type is studied from the logging response character of every kind of Reservoir type,
Judgment criteria is summarized, sensitive instruction parameter is proposed, and form software module, outputs Reservoir type indicative curve.For
The comprehensive characterization content in cave is comprehensive, has not only included qualitative cavern filling object genetic type and lithology type identification, but also including semidefinite
The cavern filling degree evaluation of amount can be realized the thoroughly evaluating in the disconnected solution oil reservoir cave of carbonate rock.
Detailed description of the invention
Fig. 1 is the GR-RS cross plot in cave and the identification of other Reservoir types.
Fig. 2 is the AC-CNL cross plot in cave and the identification of other Reservoir types.
Fig. 3 is cavern filling object genetic type Vsh-RS cross plot.
Fig. 4 is cavern filling object lithology discriminant DEN-RS cross plot.
Fig. 5 is cavern filling object lithology discriminant GR-RS cross plot.
Fig. 6 is that cavern filling degree identifies plate.
Fig. 7 is Z well cavern filling object, filling operation logging Application instance graph.
Fig. 8 is functional block diagram of the present invention.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.
A kind of disconnected solution oil reservoir cave Comprehensive Log Evaluation of carbonate rock of the present invention, Comprehensive Evaluation of Well Logging system master
Module is controlled by calling the Reservoir types identification modules such as cave to realize the judgement of Reservoir type, calls cavern filling object genetic type
Identification module realizes the judgement of charges genetic type, and cavern filling species type discrimination module is called to realize charges lithology type
Judgement, call cavern filling degree evaluation module realize filling operation calculating；It is comprised the concrete steps that:
The first step carries out the judgement of Reservoir type；Log data is inputted, according to deep lateral resistivity-natural gamma cross plot knot
It closes fracture porosity constraint and judges Reservoir type；Natural gamma GR, deep lateral resistivity RD, fracture porosity are inputted in the module
PORF curve exports disconnected Reservoir type and differentiates indicative curve CAVE_2, identifies cave according to curve of output feature；
Second step carries out the judgement of cavern filling object genetic type；Log data is inputted, shale content is calculated, is contained according to shale
The shallow lateral cross plot of amount-and its discrimination standard judge that charges genetic type is differentiated；Shallow lateral resistance is inputted in the module
Rate RS, density DEN, shale content SH and Reservoir type differentiate instruction CAVE_2 curve, Filler curve are exported, according to output
Curvilinear characteristic judges charges genetic type；
Third step carries out the judgement of cavern filling object lithology type；Log data is inputted, according to 6 kinds of cross plots and its differentiates mark
Standard judges charges lithology type；The shallow lateral resistivity RS of input, deep lateral resistivity RD, natural gamma GR, close in the module
DEN, interval transit time AC and neutron CNL are spent, packing curve is exported, charges lithology class is judged according to curve of output feature
Type；
4th step carries out the calculating of cavern filling degree；Log data is inputted, gamma relative amount is calculated, according to respective formula
Filling operation indicative curve is calculated, then filling operation comprehensive descision is obtained by the filling operation criteria for classifying；In filling operation meter
It calculates and inputs KTH, GR, CAVE_2 curve in module, export VUG1, VUG2 curve, inputted in filling operation type identification module
Curve VUG1, VUG2 curve, curve of output VUGt curve；According to a certain cave of filling operation indicative curve comprehensive descision of output
Overall filling operation.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and the differentiation that cave is exported in the first step refers to
Show realized on the basis of the discrimination standard by establishing different reservoir spaces；Fracture and cave reservoir reservoir space log response
Feature has differences with the difference of reservoir space type, passes through al-lateral resistivity, natural gamma, compensated neutron and sound wave
GR-RS and AC-CNL cross plot is established in time difference logging method；Wherein, in GR-RS cross plot cave deep lateral resistivity with from
There are notable differences for right gamma, and the sound wave in cave and neutron well logging also have difference with other Reservoir types in AC-CNL cross plot
It is different, the discrimination standard of different reservoir spaces is established using two cross plots.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, the Reservoir types identification module such as cave fortune
Cave differentiation and comprehensive analysis are carried out with RBF neural network algorithm；RBF is the three-layer forward networks with single hidden layer, first layer
For input layer, it is made of the log data sensitive to Reservoir type；The second layer is hidden layer, the transformation letter of neuron in hidden layer
Number i.e. radial basis function is the non-negative linearity function to central point radial symmetric and decaying, which is local acknowledgement's function, than
The originally function value of global response；Third layer is output layer, is responded to input data, is output reservoir class herein
The differentiation in the differentiation of type, especially cave.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and charges genetic type is sentenced in second step
Other establishment of standard method is: the charges of different origins have different logging response characters, wherein the depth bilaterally resistance
Rate, gamma ray log response are more sensitive, and there is also very big difference, shale contents to be asked by natural gamma for corresponding shale content
It takes, to construct the cross plot of cavern filling object different origins type；Cavern filling is constructed using Vsh and shallow lateral resistivity
Object genetic type identifies line of demarcation, and expression formula is respectively as follows:
。
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, and charges lithology type is sentenced in third step
Other establishment of standard method is: different lithology charges have different logging response characters, according to shale, sand shale, chiltern,
The logging response character of 5 kinds of lithology charges of breccia and calcite, utilizes natural gamma GR, deep lateral resistivity RD, shallow side
To resistivity RS, interval transit time AC, neutron CNL and density DEN, combine two-by-two construct respectively 6 cave difference charges at
Because of type identification plate, to establish the criteria for interpretation of cavern filling object Lithology Discrimination.
The disconnected solution oil reservoir cave Comprehensive Log Evaluation of the carbonate rock will be studied according to filling operation in cave
Area cave is divided into unfilled, half filling and three kinds of situations of full-filling.
The carbonate rock breaks solution oil reservoir cave Comprehensive Log Evaluation, the 4th step cavern filling degree evaluation mould
Block implementation steps:
Firstly, when using natural gamma GR, deep lateral resistivity RD, shallow lateral resistivity RS, neutron CNL, density DEN and sound wave
Poor AC is intersected two-by-two, establishes the interpretation chart of cave difference filling operation respectively；
Secondly, it is preferred that sensitive parameter of the natural gamma GR as reflection cave difference filling operation, and calculates cavern filling degree；
Define a parameter IVUG, referred to as natural gamma relative value carries out quantitatively characterizing to cavern filling degree:
(3)
In formula, X is gamma ray curve value, XminFor natural gamma limestone baseline value, XmaxThe gamma in cave is filled for pure shale
Maximum value；
Finally, establishing cavern filling degree interpretation chart and standard；Cavern filling degree is higher, IVUGValue increases, and utilizes the parameter
The interpretation chart of cavern filling degree can be obtained with shallow lateral resistivity, and establish the indicateing arm of cave difference filling operation
It is quasi-.
It responds in conjunction with the log response mechanism and practical logging of carbonate rock different reservoir type, is realized based on log data
The explanation of cave reservoir and fine characterization, and form processing module.Specific embodiment:
One, the identification in cave
(1) crossplot chart and Study of Sensitivity
Fracture and cave reservoir reservoir space logging response character has differences with the difference of reservoir space type.Than more sensitive
Logging method has al-lateral resistivity, natural gamma, compensated neutron and interval transit time.If Fig. 1 is GR-RS cross plot, in cave
There are notable differences with natural gamma for deep lateral resistivity；Fig. 2 is AC-CNL cross plot, acoustic logging, the neutron well logging in cave
Also variant with other well loggings.Using two cross plots, cave type reservoir can be distinguished relatively easily, GR-RS cross plot
It is more better than AC-CNL cross plot effect.The discrimination standard of different reservoir spaces is established using two cross plots.
The instruction of 1 fracture hole carbonate rock different reservoir type identification of table
| Reservoir Body space type | GR(API) | RD(Ω·m) | AC(g/cm3) | CNL(%) | Indicated value |
| Compacted zone | <12 | >900 | 48~49.5 | <0.25 | 0 |
| Fracture reservoir | 9~15 | 150~600 | 49.5~53 | 0.3~0.81 | 1 |
| Cranny and cave reservoir | 4~12 | 400~1200 | 48~51.6 | 0.3~0.81 | 2 |
| Crack-cranny and cave reservoir | 9~15 | 30~100 200~400 | 48.7~55 | 0.1~1.51 | 3 |
| Fill cave | 15~150 | 0~300 | 48~60 | 0.2~8.0 | 4 |
| Unfilled cave | 6~16 | <30 | 52~75 | 1.3~9.0 | 5 |
In addition, also using RBF neural network algorithm to improve the precision of the Reservoir types such as cave identification.RBF is that have list hidden
The three-layer forward networks of layer.First layer is input layer, is made of the log data sensitive to Reservoir type.The second layer is hiding
Layer, transforming function transformation function, that is, radial basis function of neuron is the non-negative linearity letter to central point radial symmetric and decaying in hidden layer
Number, which is local acknowledgement's function, than the function value of original global response.Third layer is output layer, is to input data
It responds, is the differentiation for exporting Reservoir type, the especially differentiation in cave herein.
In Reservoir type differentiation, select GR, RD, the AC and CNL log data sensitive to Reservoir type as input, root
The Reservoir type determined according to geological informations such as well logging, drilling wells is as output.Using the input of known results, output data as number
According to collection, random selection 80% is used as training set, and 20% is used as test set.By training with after test, best network and its ginseng are determined
Number.Finally judged using optimum network and the unknown Reservoir type log data of input.
(2) comprehensive analysis
Comprehensive analysis is carried out using intersection drawing method and its criterion of identification, RBF neural, is split in addition, being additionally added in differentiation
Seam identification information is constrained, and input curve is natural gamma, deep lateral resistivity and fracture porosity.Finally, to reservoir
The identification and instruction of type carry out comprehensive analysis and obtain differentiation result.
Two, charges genetic type identifies
(1) cross plot and Study of Sensitivity
According to the difference of the origin cause of formation, cavern filling object can be divided into mechanical sediment, gravitational collapse deposit and chemical precipitation filling
Object three categories.The charges of different origins have different logging response characters, wherein depth al-lateral resistivity, natural gamma
Log response is more sensitive, and there is also very big differences for corresponding shale content.Shale content is usually sought by natural gamma.
According to the logging response character of different charges genetic types, the friendship of cavern filling object different origins type is constructed
It can plate.Fig. 1 and 2 is the identification plate established using Vsh and shallow lateral resistivity.From plate as can be seen that mechanical sediment,
Gravitational collapse deposit has the raising with resistivity, the trend that shale reduces to chemical precipitates.Mechanical sediment is general
Based on the filling of sand shale, resistivity is lower, and shale is higher；Gravitational collapse deposit is based on breccia, resistivity high level；Change
Sediment is learned based on calcite, shows as low shale, high resistivity.Unfilled cave shows as low natural gamma, low resistance
The feature of rate.Indicative curve, table are identified using cavern filling object genetic type identification module building cavern filling object genetic type
It is respectively as follows: up to formula
The identification instruction of 2 cavern filling object genetic type of table
| Charges type | Vsh(%) | RS(Ω·m) | DEN(g/cm3) | Indicated value |
| It is unfilled | <Y1 | <50 | 2.29~2.24 | 1 |
| Mechanical deposit filling | Y1<Vsh<Y2 | <100 | 1.86~2.43 | 2 |
| Gravitational collapse accumulation | >Y2 | <400 | 2.32~2.74 | 3 |
| Chemical precipitation filling | <5% | >4000 | >2.71 | 4 |
(2) comprehensive analysis and computing module
Write the identification and instruction that module carries out cavern filling object genetic type using the above method, input curve be it is shallow lateral,
Compensation density, shale content and Reservoir type instruction.Shale content is calculated by natural gamma.
Three, cavern filling object lithology discriminant
(1) log response Study of Sensitivity
Charges can be divided into 5 classes by lithology type by carbonate rock cave type reservoir charges, be respectively shale, sand shale,
Chiltern, breccia and calcite.Different lithology charges have different logging response characters, have than more sensitive logging method
Natural gamma (GR), deep lateral resistivity (RD), shallow lateral resistivity (RS) and interval transit time (AC), neutron (CNL), density
(DEN) also more sensitive.
According to shale, sand shale, chiltern, 5 kinds of lithology charges of breccia and calcite logging response character, utilize
GR, RD, RS, AC, CNL, DEN are combined two-by-two establishes 6 cave difference charges genetic type identification plates respectively.Figure 4 and 5
For two typical crossplots.Find out from crossplot chart, cavern filling shale, sand shale, chiltern, breccia to calcite
When, shale content gradually decreases, and shallow lateral resistivity is gradually increased.Shale, sand shale, chiltern can be collectively referred to as the filling of sand shale,
Show as natural gamma high level, al-lateral resistivity low value.With the increase of shale content, interval transit time increases, and density value reduces.
When filling breccia, natural gamma is middle low value, and depth al-lateral resistivity is high level, and interval transit time is low, and middle subvalue is low, density
It is high；When filling calcite, natural gamma is low, and al-lateral resistivity is high, and interval transit time is small, and neutron is low, and density is high.
According to above-mentioned cross plot, the discrimination standard of cavern filling object Lithology Discrimination is realized, as shown in table 3.
The instruction of 3 cavern filling object Lithology Discrimination of table
| Charges type | GR(API) | RS(Ω∙m) | DEN(g/cm3) | Indicated value |
| It is unfilled | < 20 | < 6 | 2.29~2.24 | 1 |
| Shale filling | 30~110 | 0.5~25 | 1.86~2.43 | 2 |
| The filling of sand shale | 15~95 | 0~200 | 2.32~2.74 | 3 |
| Chiltern filling | 15~55 | 25~120 | 2.23~2.64 | 4 |
| Breccia filling | 7~20 | 40~5000 | 2.69~2.72 | 5 |
| Calcite filling | 2~8 | >7200 | 2.73~2.75 | 6 |
(3) comprehensive analysis and computing module
Module cavern filling object lithology type is write using the above method to be identified and indicated, input curve be the depth it is lateral,
Natural gamma, compensation density, interval transit time and compensated neutron.
Four, cavern filling degree evaluation
(1) logging response character and Study of Sensitivity
The storage and collection performance in cave additionally depends on the filling operation in cave other than related with the size and connectivity in cave,
Only unfilled cave and half filling cave just have the ability of Reservoir Fluid.According to filling operation in cave, area hole will be studied
Cave type reservoir division is unfilled, half filling and three kinds of situations of full-filling.The difference of cavern filling degree, natural gamma, the depth
There are great differences for al-lateral resistivity, interval transit time, middle subvalue, density log etc..
(2) cavern filling degree calculates
Utilize natural gamma (GR), depth al-lateral resistivity (RD, RS), neutron (CNL), density (DEN) and interval transit time
(AC) it is intersected two-by-two, establishes the identification plate of cave difference filling operation type respectively.By intersection identification plate it is found that certainly
Right gamma (GR), neutron (CNL) are more sensitive to the filling operation in cave, and cavern filling degree is higher, and natural gamma value is higher,
Middle subvalue is also higher.It is therefore preferable that sensitivity curve of the natural gamma (GR) as reflection cave difference filling operation, and calculate hole
Cave filling operation.
Define a parameter IVUG, referred to as natural gamma relative value carries out quantitatively characterizing to cavern filling degree:
(3)
In formula, X is gamma ray curve value；XminFor natural gamma limestone baseline value. XmaxThe gamma in cave is filled for pure shale
Maximum value.
As cavern filling degree is higher, IVUGValue increases, and cavern filling can be obtained using the parameter and shallow lateral resistivity
Degree identified amount version, is shown in Fig. 6, and establishes the instruction standard of cave difference filling operation, as shown in table 4.
4 cavern filling degree criterion of identification of table
| Cave filling extent type | IVUG(%) | Filling extent (IVUGt) instruction assignment |
| It is unfilled | 0~20 | 1 |
| Half fills | 20~60 | 2 |
| Full-filling | 60~100 | 3 |
(3) comprehensive analysis and computing module
The identification and instruction that module carries out cavern filling degree are write using the above method.Firstly, carrying out cavern filling degree
Quantitative to calculate, input curve is no uranium gamma, natural gamma, Reservoir type indicate, exporting result is filling operation instruction.So
Afterwards, filling operation type identification is carried out, input curve is filling operation indicative curve, and output result is that filling operation type refers to
Show.
Five, specific steps
(1) firstly, carrying out the judgement of Reservoir type.Log data is inputted, according to deep lateral resistivity-natural gamma cross plot knot
It closes fracture porosity constraint and judges that Reservoir type is differentiated.GR, RD, PORF curve are inputted in the module, and output CAVE_2 is bent
Line judges that Reservoir type, emphasis export the differentiation instruction in cave according to curve of output feature.
(2) then, the judgement of cavern filling object genetic type is carried out.Log data is inputted, shale content is calculated, according to mud
The shallow lateral cross plot of matter content-and its discrimination standard differentiate charges genetic type.In the module input RS, DEN,
SH, CAVE_2 curve export Filler curve, judge charges genetic type according to curve of output feature.
(3) secondly, carrying out the judgement of cavern filling object lithology type.Log data is inputted, according to 6 kinds of cross plots and its is sentenced
Other standard judges that charges lithology type is differentiated.RS, RD, GR, DEN, AC, CNL, CN curve, output are inputted in the module
Packing curve judges charges lithology type according to curve of output feature.
(4) finally, carrying out the calculating of cavern filling degree.Log data is inputted, gamma relative amount is calculated, according to corresponding
Formula calculating filling operation indicative curve passes through the filling operation criteria for classifying again and obtains filling operation indicative curve.In filling operation
KTH, GR, CAVE_2 curve are inputted in computing module, exports VUG1, VUG2 curve, are inputted in filling operation discrimination module bent
Line VUG1, VUG2 curve, curve of output VUGt curve.According to a certain cave of filling operation curve numerical value comprehensive descision of output
Overall filling operation.
Instance analysis
Z well is a bite exploratory well of Ordovician of Tahe oil, has carried out data using above scheme and the device of exploitation (module)
Processing, respectively identifies cavernous formation, and charges genetic type, charges lithology type and filling has been calculated
The indicative curves such as degree.Fig. 7 is the comprehensive log interpretation result map in cave, is a sand in 5555~5559.5m well log interpretation
Mud fills cave, and filling operation is full-filling cave, matches with well logging conclusion 60~85%；In 5587.5~5599.5m
Well log interpretation is that a sand mud fills cave, and filling operation, for half filling cave, matches 20~40% with well logging conclusion；?
5599.5~5628m is construed to the filling of sand mud, and filling operation is full-filling cave, the explanation results and well logging knot 70~95%
By matching.
The present invention is not limited to above-mentioned preferred forms, anyone obtain under the inspiration of the present invention other it is any with
The identical or similar product of the present invention, is within the scope of the present invention.
Claims (7)
- A kind of solution oil reservoir cave Comprehensive Log Evaluation 1. carbonate rock breaks, it is characterised in that: Comprehensive Evaluation of Well Logging system Main control module calls cavern filling object origin cause of formation class by calling the Reservoir types identification modules such as cave to realize the judgement of Reservoir type Type identification module realizes the judgement of charges genetic type, and cavern filling species type discrimination module is called to realize charges lithology class The judgement of type calls cavern filling degree evaluation module to realize the calculating of filling operation；It is comprised the concrete steps that:The first step carries out the judgement of Reservoir type；Log data is inputted, according to deep lateral resistivity-natural gamma cross plot knot It closes fracture porosity constraint and judges Reservoir type；Natural gamma GR, deep lateral resistivity RD, fracture porosity are inputted in the module PORF curve exports disconnected Reservoir type and differentiates indicative curve CAVE_2, identifies cave according to curve of output feature；Second step carries out the judgement of cavern filling object genetic type；Log data is inputted, shale content is calculated, is contained according to shale The shallow lateral cross plot of amount-and its discrimination standard judge that charges genetic type is differentiated；Shallow lateral resistance is inputted in the module Rate RS, density DEN, shale content SH, CAVE_2 curve export Filler curve, judge charges according to curve of output feature Genetic type；Third step carries out the judgement of cavern filling object lithology type；Log data is inputted, according to 6 kinds of cross plots and its differentiates mark Standard judges charges lithology type；The shallow lateral resistivity RS of input, deep lateral resistivity RD, natural gamma GR, close in the module DEN, interval transit time AC, neutron CNL are spent, packing curve is exported, charges lithology type is judged according to curve of output feature；4th step carries out the calculating of cavern filling degree；Log data is inputted, gamma relative amount is calculated, according to respective formula Filling operation indicative curve is calculated, then filling operation comprehensive descision is obtained by the filling operation criteria for classifying；In filling operation meter It calculates and inputs KTH, GR, CAVE_2 curve in module, export VUG1, VUG2 curve, inputted in filling operation type identification module Curve VUG1, VUG2 curve, curve of output VUGt curve；According to a certain cave of filling operation indicative curve comprehensive descision of output Overall filling operation.
- The solution oil reservoir cave Comprehensive Log Evaluation 2. carbonate rock according to claim 1 breaks, it is characterised in that: the The differentiation instruction that cave is exported in one step is realized on the basis of the discrimination standard by establishing different reservoir spaces；Fracture hole Reservoir Body reservoir space logging response character has differences with the difference of reservoir space type, by al-lateral resistivity, GR-RS and AC-CNL cross plot is established in natural gamma, compensated neutron and interval transit time logging method；Wherein, in GR-RS cross plot Middle cave deep lateral resistivity and natural gamma are there are notable difference, the sound wave in cave and neutron well logging in AC-CNL cross plot Also variant with other Reservoir types, the discrimination standard of different reservoir spaces is established using two cross plots.
- The solution oil reservoir cave Comprehensive Log Evaluation 3. carbonate rock according to claim 1 breaks, it is characterised in that: hole The Reservoir types identification module such as cave carries out cave differentiation and comprehensive analysis with RBF neural network algorithm；RBF is that have single hidden layer Three-layer forward networks, first layer is input layer, is made of the log data sensitive to Reservoir type；The second layer is hidden layer, Transforming function transformation function, that is, radial basis function of neuron is the non-negative linearity function to central point radial symmetric and decaying in hidden layer, should Function is local acknowledgement's function, than the function value of original global response；Third layer is output layer, is to make sound to input data It answers, is the differentiation for exporting Reservoir type, the especially differentiation in cave herein.
- The solution oil reservoir cave Comprehensive Log Evaluation 4. carbonate rock according to claim 1 breaks, it is characterised in that: the Charges Determination of Genetic Types establishment of standard method is in two steps: the charges of different origins have different log responses special Sign, wherein depth al-lateral resistivity, gamma ray log response are more sensitive, and there is also very big differences for corresponding shale content Different, shale content is sought by natural gamma, to construct the cross plot of cavern filling object different origins type；Using Vsh with Shallow lateral resistivity building cavern filling object genetic type identifies line of demarcation, and expression formula is respectively as follows:Y1=20.223RS-2.056 (1)Y2=80.924RS-0.632 (2) 。
- The solution oil reservoir cave Comprehensive Log Evaluation 5. carbonate rock according to claim 1 breaks, it is characterised in that: the Charges lithology type identification establishment of standard method is in three steps: different lithology charges have different log responses special Sign, according to shale, sand shale, chiltern, 5 kinds of lithology charges of breccia and calcite logging response character, utilize nature gal Horse GR, deep lateral resistivity RD, shallow lateral resistivity RS, interval transit time AC, neutron CNL and density DEN, combine difference two-by-two 6 cave difference charges genetic type identification plates are constructed, to establish the criteria for interpretation of cavern filling object Lithology Discrimination.
- The solution oil reservoir cave Comprehensive Log Evaluation 6. carbonate rock according to claim 1 breaks, it is characterised in that: root According to filling operation in cave, research area cave is divided into unfilled, half filling and three kinds of situations of full-filling.
- The solution oil reservoir cave Comprehensive Log Evaluation 7. carbonate rock according to claim 1 breaks, it is characterised in that: the Four step cavern filling degree evaluation module implementation steps:Firstly, when using natural gamma GR, deep lateral resistivity RD, shallow lateral resistivity RS, neutron CNL, density DEN and sound wave Poor AC is intersected two-by-two, establishes the interpretation chart of cave difference filling operation respectively；Secondly, it is preferred that sensitive parameter of the natural gamma GR as reflection cave difference filling operation, and calculates cavern filling degree； Define a parameter IVUG, referred to as natural gamma relative value carries out quantitatively characterizing to cavern filling degree:(3)In formula, X is gamma ray curve value, XminFor natural gamma limestone baseline value, XmaxThe gamma in cave is filled for pure shale Maximum value；Finally, establishing cavern filling degree interpretation chart and standard；Cavern filling degree is higher, IVUGValue increases, and utilizes the parameter The interpretation chart of cavern filling degree can be obtained with shallow lateral resistivity, and establish the indicateing arm of cave difference filling operation It is quasi-.
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