CN106223942A - A kind of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction - Google Patents
A kind of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction Download PDFInfo
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- CN106223942A CN106223942A CN201610730484.4A CN201610730484A CN106223942A CN 106223942 A CN106223942 A CN 106223942A CN 201610730484 A CN201610730484 A CN 201610730484A CN 106223942 A CN106223942 A CN 106223942A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
Abstract
The invention provides a kind of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction, comprise the following steps: (1) core sample shale content measures；(2) shale sensitivity curve is preferred: determine the sensitivity curve that Conglomerate Reservoir shale content calculates as shale content with described compensated neutron porosity logging curve and described compensated density log curve；(3) curve normalized: on the basis of the sensitivity curve that the shale content determined in step (2) calculates, respectively described compensated neutron porosity logging curve and described compensated density log curve are normalized；(4) structure shale content calculates parameter (NZCS)；(5) computation model is set up and optimizes.Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction of the present invention, eliminate lithology and the anisotropism impact on its result of calculation during Conglomerate Reservoir shale content calculates, improve the computational accuracy of reservoir shale content.
Description
Technical field
The invention belongs to oil development reservoir engineering technical field, especially relate to a kind of gravel based on Well logging curve reconstruction
Rock oil reservoir shale content computational methods.
Background technology
Shale content is an important parameter in evaluating reservoir, and it accurately calculates the judgement for depositional environment, infiltration
The foundation of rate model and the research of micropore structure suffer from important directive significance.Conglomerate Reservoir is due to nearly thing source, Duo Shui
System and quick and various depositional environment cause reservoir heterogeneity serious, and complex lithology is changeable, and pore structure presents complex mode
Distribution characteristics, above reservoir characteristics adds the difficulty of shale content quantitative assessment.It addition, current domestic each oil field has been entered
Entering to tertiary phase based on polymer flooding, Conglomerate Reservoir is no exception, due to the key problem of polymer flooding be for
The polymer molecular weight of the reservoir Optimum Matching of different permeability ranks, in order to reach not only to improve oil recovery but also do not destroy storage
The purpose of layer seepage flow, permeability be accurately calculated as the poly-key factor driving scheme success.For heterogeneous body
The Conglomerate Reservoir that property is serious and complex lithology is changeable, owing to the size of shale content and distribution form can change the hole of reservoir
Structure, and then affect permeability, therefore, the key factor being accurately calculated as Conglomerate Reservoir polymer flooding of shale content.
And lithology uniform sandstone oil reservoir, shale content calculating side of based on log weak currently for anisotropism
Method comparative maturity, the different computational accuracies of model and the suitability of method can reach the requirement that practical logging is explained.
But, for the computational methods of Conglomerate Reservoir shale content, previous work was also carried out some and explores and discuss.Si Mali is strong
" high gamma stratum based on curve Reconstruction shale content computational methods " (" logging technique ") delivered is based on natural gamma spectra
Well logging, utilizes the thinking of curve combination to construct new gamma curve without uranium, can effectively calculate shale content；Hou Lianhua etc.
" turbidite reservoir shale content computational methods and application thereof " (" the University of Petroleum's journal ") delivered, research finds, due to radiation
Property mineral and the impact of formation water salinity, natural gamma and spontaneous potential curve can not reflect reservoir shale content feelings truly
Condition, it is proposed that utilize the method that the resistivity curve after correction asks for shale content.But, of both above method existence not
Foot, one is that the recent research about conglomerate Sedimentology shows, for the Conglomerate Reservoir in nearly thing source, owing to rock particles does not has
Through carrying, sorting and the rounding of long-distance, radioactive mineral presents the distribution characteristics of randomness, high gamma sand often occurs
Rock or low gamma mud stone, gamma curve cannot function as the sensitive parameter that shale content calculates；Two is for complex lithology and non-
The Conglomerate Reservoir that homogeneity is serious, the content of detrital grain and grade (lithology) are much larger than shale content to the impact that reservoir is electrical
Impact, the excursion of Conglomerate Reservoir reservoir resistivity is bigger, between 15～700 Ω m, causes reservoir resistivity
The principal element of so big difference is conglomerate lithology rather than shale content and property of pore fluid, and resistivity curve is to shale not
Sensitivity, computational accuracy ratio is relatively low.Drive scheme it addition, Conglomerate Reservoir is poly-reservoir permeability Explanation Accuracy had higher requirement,
And the accurate calculating of shale content affects the precision of penetration rate model.Therefore, response characteristic based on log is set up
High-precision Conglomerate Reservoir shale content computation model becomes poly-and drives the key factor that scheme is implemented smoothly.
Summary of the invention
In order to eliminate the impact that Conglomerate Reservoir shale content is calculated by anisotropism and complex lithology, improve shale content fixed
The precision that amount is evaluated, it is an object of the invention to provide a kind of Conglomerate Reservoir shale content calculating side based on Well logging curve reconstruction
Method, based on the reservoir characteristic of Conglomerate Reservoir, with core experiment data as foundation, relative analysis difference curve shale content
Log response, preferably sensitivity curve, reconstruct shale instruction parameter, set up high-precision shale content computation model, and for oozing
The optimization of rate model provides corresponding technical support thoroughly.
The technical solution used in the present invention is:
A kind of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction, comprise the following steps:
(1) core sample shale content measures: the geologic setting in binding district and reservoir characteristic, based on log
Response characteristic, chooses typical Conglomerate Reservoir core sample from sealed coring well, and then carries out shale content to choosing sample
Mensuration, and the measurement numerical value of shale content is demarcated on described log, it is ensured that the rock of shale content is measured in experiment
The heart degree of depth is consistent with the described log degree of depth；
(2) shale sensitivity curve is preferred: comprehensively analyze the response characteristic of Conglomerate Reservoir log, and and step
(1) in, the experimental analysis data of shale content contrast, and find Conglomerate Reservoir shale content and compensated neutron porosity logging
The radial extent difference correlation of curve and compensated density log curve is relatively good, accordingly, it is determined that Conglomerate Reservoir shale content and institute
State compensated neutron porosity logging curve and sensitivity curve that described compensated density log curve calculates as shale content；
(3) curve normalized: on the basis of the sensitivity curve that the shale content determined in step (2) calculates, respectively
Described compensated neutron porosity logging curve and described compensated density log curve are normalized, see formula (1) and
Formula (2)；
Compensated neutron porosity curve normalization computing formula:
CNLgy=(CNL+15)/(45+15) (1)
Compensation density curve normalization computing formula:
DENgy=(DEN-1.95)/(2.95-1.95) (2)
In formula, CNLgyAnd DENgyRepresent the neutron porosity after normalization and density value, dimensionless respectively；CNL is reservoir
Compensated neutron porosity logging value, %；DEN is reservoir density log value, g/cm3；
(4) structure shale content calculating parameter (NZCS): i.e. normalization post-compensation neutron porosity curve and compensation density
The difference of curve, thus the radial extent portraying two described sensitivity curves is poor, sees formula (3)；
It is as follows that shale content calculates parameter equation:
NZCS=CNLgy-DENgy (3)
In formula, NZCS-shale content calculates parameter, dimensionless；
(5) computation model is set up and optimizes: utilizes shale content described in step (4) to calculate parameter (NZCS) and divides with rock core
The shale content of analysis sets up transformational relation between the two, determines the computation model of shale content；
(6) precision of described computation model is evaluated, after optimization can with the shale content of quantitative Analysis Conglomerate Reservoir,
And the foundation for penetration rate model provides variable parameter.
Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction of the present invention, wherein, in step (1)
The selection of described sample is distributed in DIFFERENT DEPOSITIONAL ENVIRONMENTS, different layers position and different lithology, it is ensured that experimental data can take into account spy
Different property and the principle of universality.
Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction of the present invention, wherein, step (1) is adopted
By the measuring method of the laboratory grain size analysis mensuration to choosing sample and carry out shale content.
The method have the benefit that
Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction of the present invention, not only eliminate conglomerate
Lithology and the anisotropism impact on its result of calculation during the calculating of oil reservoir shale content, improve the meter of reservoir shale content
Calculate precision；And on the basis of shale content accurately calculates, the foundation for the lower penetration rate model of shale constraint provides technology
Support.
Accompanying drawing explanation
Fig. 1 is the flow chart of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction of the present invention；
Eastern 1 district gram Xia Zu I district (T71721 well) the shale content sensitivity curve comparison diagram of Fig. 2 a seven；
Eastern 1 district gram Xia Zu II district (T71740 well) the shale content sensitivity curve comparison diagram of Fig. 2 b seven；
Eastern 1 district gram Xia Zu III district (T71839 well) the shale content sensitivity curve comparison diagram of Fig. 2 c seven.
Below in conjunction with specific embodiments and the drawings, the invention will be further described.
Detailed description of the invention
A kind of Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction, comprise the following steps:
(1) core sample shale content measures: to organize the conglomerate oil in I, II and III district under 1 district gram, In Karamay Oil Radix Notoginseng east
As a example by Tibetan, the geologic setting in binding district and reservoir characteristic, response characteristic based on Logging Curves, such as Fig. 2 a, 2b and
Shown in 2c, choosing typical Conglomerate Reservoir core sample from sealed coring well, the selection of described sample is distributed in not synsedimentary
Environment, different layers position and different lithology, it is ensured that experimental data can take into account the principle of particularity and universality, and then uses real
Test the measuring method of room grain size analysis to choosing sample and carry out the mensuration of shale content, and the measurement numerical value mark of shale content
Determine on described log, it is ensured that the rock core degree of depth that shale content is measured in experiment is consistent with the described log degree of depth；
(2) shale sensitivity curve is preferred: comprehensively analyze the response characteristic of Conglomerate Reservoir log, and and step
(1) in, the experimental analysis data of shale content contrast, and find Conglomerate Reservoir shale content and compensated neutron porosity logging
The radial extent difference correlation of curve and compensated density log curve is relatively good；Understand from such as Fig. 2 a, 2b and 2c, survey in standard
Under well scale, amplitude difference is the biggest, and shale content is the highest, and reservoir pore space and seepage flow are gradually deteriorated；Amplitude difference is the least, and shale contains
Measure the lowest, the seepage flow of reservoir is affected the least.Analyze reason and all use nuclear logging mainly due to both logs
Principle, relative to sound wave and electrical log, it is affected relatively small by rock particles size and anisotropism, to shale content
Indicative function higher, accordingly, it is determined that Conglomerate Reservoir shale content and described compensated neutron porosity logging curve and described benefit
Repay the sensitivity curve that density log curve calculates as shale content；
(3) curve normalized: on the basis of the sensitivity curve that the shale content determined in step (2) calculates, respectively
Described compensated neutron porosity logging curve and described compensated density log curve are normalized, see formula (1) and
Formula (2), owing to described compensated neutron porosity logging curve and the logging principle of described compensated density log curve and physics are anticipated
Justice is different from, it is thus impossible to the difference directly utilizing original log carries out the calculating of shale content.In order to eliminate two
The physical significance of described log, and make the left and right scale of described log keep consistent, to two described well logging songs
Line is normalized, and eliminates the physical meaning of described sensitivity curve, only represents the relative size of curve numerical value；
Compensated neutron porosity curve normalization computing formula:
CNLgy=(CNL+15)/(45+15) (1)
Compensation density curve normalization computing formula:
DENgy=(DEN-1.95)/(2.95-1.95) (2)
In formula, CNLgyAnd DENgyRepresent the neutron porosity after normalization and density value, dimensionless respectively；CNL is reservoir
Compensated neutron porosity logging value, %；DEN is reservoir density log value, g/cm3；
(4) structure shale content calculates parameter (NZCS): normalization post-compensation neutron porosity curve is bent with compensation density
The difference of line, thus the radial extent portraying two described sensitivity curves is poor, sees formula (3)；
It is as follows that shale content calculates parameter equation:
NZCS=CNLgy-DENgy (3)
In formula, NZCS is that shale content calculates parameter, dimensionless；
(5) computation model is set up and optimizes: utilizes shale content described in step (4) to calculate parameter (NZCS) and divides with rock core
The shale content of analysis sets up transformational relation between the two, determines the shale content computation model of different geologic division, is shown in Table 1,
And result of calculation is analyzed, the relative error that three geologic division shale contents calculate all control 10% with
In, meet the required precision that practical logging is explained；
The different subregion shale content computation model of table 1 and result of calculation
(6) precision of described computation model is evaluated, after optimization can with the shale content of quantitative Analysis Conglomerate Reservoir,
And the foundation for penetration rate model provides variable parameter.Shale content evaluation result can be as the weight affecting permeability
Want factor to participate in its model to set up, i.e. calculation model of permeability under shale retrains, to improve the calculating essence of reservoir permeability
Degree, can provide geologic parameter accurately for the design of polymer flooding scheme.
The computation model utilizing the shale content that the present embodiment sets up calculates seven east1The shale organizing Conglomerate Reservoir under Qu Ke contains
Amount, has reached the required precision of well log interpretation.It addition, establish the penetration rate model of two kinds of Conglomerate Reservoirs, one is at shale
Penetration rate model under content constraint, i.e. utilizes effecive porosity and two parameter multiple regressions of shale content；Another kind is only
Consider the effecive porosity impact on permeability, use single factor test linear regression.The result of calculation of two kinds of penetration rate models understands
Ground show, the computational accuracy of dual relief valve be higher than unifactor model, the former to gram under organize reservoir mean permeability calculate knot
Fruit is 966.7 × 10-3μm2, the latter is 2998.4 × 10-3μm2, and core analysis meansigma methods is 868.1 × 10-3μm2, calculate essence
Degree is significantly improved, it is ensured that the poly-smooth enforcement driving scheme.
Example discussed above is only to be described the preferred embodiment of the present invention, not to the scope of the present invention
Being defined, on the premise of designing spirit without departing from the present invention, those of ordinary skill in the art are to technical scheme
The various deformation made and improvement, all should fall in the protection domain that claims of the present invention determines.
Claims (3)
1. Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction, it is characterised in that: comprise the following steps:
(1) core sample shale content measures: the geologic setting in binding district and reservoir characteristic, response based on log
Feature, chooses typical Conglomerate Reservoir core sample from sealed coring well, and then to choosing sample and carry out the survey of shale content
Fixed, and the measurement numerical value of shale content is demarcated on described log, it is ensured that the rock core that shale content is measured in experiment is deep
Spend consistent with the described log degree of depth；
(2) shale sensitivity curve is preferred: comprehensively analyze the response characteristic of Conglomerate Reservoir log, and with step (1)
The experimental analysis data of middle shale content contrast, and find Conglomerate Reservoir shale content and compensated neutron porosity logging curve
Radial extent difference correlation with compensated density log curve is relatively good, accordingly, it is determined that Conglomerate Reservoir shale content and described benefit
Repay neutron porosity log curve and sensitivity curve that described compensated density log curve calculates as shale content；
(5) curve normalized: on the basis of the sensitivity curve that the shale content determined in step (2) calculates, respectively to institute
State compensated neutron porosity logging curve and described compensated density log curve is normalized, see formula (1) and formula
(2)；
Compensated neutron porosity curve normalization computing formula:
CNLgy=(CNL+15)/(45+15) (1)
Compensation density curve normalization computing formula:
DENgy=(DEN-1.95)/(2.95-1.95) (2)
In formula, CNLgyAnd DENgyRepresent the neutron porosity after normalization and density value, dimensionless respectively；CNL is that reservoir compensates
Neutron porosity log value, %；DEN is reservoir density log value, g/cm3；
(6) structure shale content calculating parameter (NZCS): i.e. normalization post-compensation neutron porosity curve and compensation density curve
Difference, thus the radial extent portraying two described sensitivity curves is poor, sees formula (3)；
It is as follows that shale content calculates parameter equation:
NZCS=CNLgy-DENgy (3)
In formula, NZCS-shale content calculates parameter, dimensionless；
(5) computation model is set up and optimizes: utilize shale content described in step (4) to calculate parameter (NZCS) and core analysis
Shale content sets up transformational relation between the two, determines the computation model of shale content；
(6) precision of described computation model is evaluated, after optimization can with the shale content of quantitative Analysis Conglomerate Reservoir, and
Foundation for penetration rate model provides variable parameter.
Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction the most according to claim 1, its feature exists
In: the selection of sample described in step (1) is distributed in DIFFERENT DEPOSITIONAL ENVIRONMENTS, different layers position and different lithology, it is ensured that experiment number
According to the principle that can take into account particularity and universality.
Conglomerate Reservoir shale content computational methods based on Well logging curve reconstruction the most according to claim 1 and 2, its feature
It is: the measuring method of step (1) employing laboratory grain size analysis carries out the mensuration of shale content to choosing sample.
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| CN107065011A (en) * | 2017-06-22 | 2017-08-18 | 东北石油大学 | A kind of curve frequencies fusion method applied to continental basins reservoir inversion |
| CN109339773A (en) * | 2018-10-09 | 2019-02-15 | 中国地质大学（北京） | Based on conglomerate matrix content well logging porosity model and its construction method and application |
| CN111042805A (en) * | 2019-12-11 | 2020-04-21 | 中国海洋石油集团有限公司 | Method for calculating formation water mineralization degree |
| CN111255435A (en) * | 2020-01-17 | 2020-06-09 | 西安石油大学 | Method for calculating shale content of complex reservoir |
| CN112541523A (en) * | 2020-11-17 | 2021-03-23 | 中海油田服务股份有限公司 | Method and device for calculating mud content |
| CN112987122A (en) * | 2019-12-13 | 2021-06-18 | 北京国双科技有限公司 | Method and device for calculating mud content, electronic equipment and storage medium |
| CN114075973A (en) * | 2020-08-13 | 2022-02-22 | 中国石油天然气股份有限公司 | Stratum element logging curve reconstruction method and device |
| CN115793094A (en) * | 2023-02-06 | 2023-03-14 | 西北大学 | Method for identifying lithology of complex shale bed through curve superposition reconstruction and application |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114075973A (en) * | 2020-08-13 | 2022-02-22 | 中国石油天然气股份有限公司 | Stratum element logging curve reconstruction method and device |
| CN114075973B (en) * | 2020-08-13 | 2024-03-01 | 中国石油天然气股份有限公司 | Stratum element logging curve reconstruction method and device |
| CN112541523A (en) * | 2020-11-17 | 2021-03-23 | 中海油田服务股份有限公司 | Method and device for calculating mud content |
| CN112541523B (en) * | 2020-11-17 | 2023-02-28 | 中海油田服务股份有限公司 | Method and device for calculating mud content |
| CN115793094A (en) * | 2023-02-06 | 2023-03-14 | 西北大学 | Method for identifying lithology of complex shale bed through curve superposition reconstruction and application |
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