CN105447762A - Calculation method for low permeability reservoir flooding information of fluid replacement - Google Patents
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Abstract
The present invention discloses a calculation method for low permeability reservoir flooding information of fluid replacement. The method comprises: 1) acquiring response features of logging before and after reservoir flooding in a region, and selecting, from the response features, natural gamma GR and acoustic interval transit time AC logging curves without significant lithological and physical changes before and after flooding; 2) selecting logging information of a model well that is not flooded, and establishing a function relationship among electrical resistivity of an original fluid in reservoir pores, natural gamma and acoustic interval transit time; 3) calculating a flooded model well in the region by using the function relationship to obtain the electrical resistivity t1 of the original fluid contained in the reservoir pores in the flooded model well, and comparing the electrical resistivity t1 with electrical resistivity t2 obtained by actual measurement to obtain an electrical resistivity variation value; 4) establishing a dividing standard of identifying a flooding level by using the electrical resistivity variation value delta Rt; and 5) according to the dividing standard of identifying the flooding level by using the electrical resistivity variation value delta Rt, established in the step 4), accurately and effectively determining flooding information of a to-be-evaluated well in the region.
Description
Technical field
The invention belongs to petroleum well logging technology field, relate to the computing method of the low-permeability oil deposit water logging information that a kind of fluid is replaced.
Background technology
Study area object reservoir properties is poor, and reservoir space is little, and factor of porosity distribution range is 4 ~ 16%, and permeability is mainly distributed in 0.1 ~ 2 × 10
-3μm
2between, belong to low porosity and permeability oil reservoir.Go through the waterflooding of more than 20 year, cause the fluid properties of reservoir, pore texture and oil and water zonation etc. to change.Along with the rising of water percentage, water out behavior is complicated, and electrically change is increasing, and water flooded grade is sentenced and known difficulty.The accurate division of water flooded grade is the problem that must solve in waterflooding oil field adjustment work, improves in recovery ratio and stable rate etc. play vital effect in oil field old.At present, Water Flooding Layer water flooded grade evaluation method is more, as logging trace qualitative recognition method, crossplot method and movable fluid analytic approach etc., but domestic each oil field is due to the difference of its geological state and Exploitation degree, current evaluation method all has region limitation, there is no a kind of computing method of low-permeability oil deposit water logging information of general fast qualitative, be difficult to apply.The division water flooded grade of reconstruct Water Flooding Layer prime stratum resistivity fast qualitative is one of effective ways, but because this respect data is less, and reconstructing method many based on a large amount of core experiment data set up, by expensive the core restriction of expense and the scarcity of core experiment analysis data, range of application is little, especially, in the secondary development of oil field old, be difficult to meet actual production demand.
Summary of the invention
The object of the invention is to the shortcoming overcoming above-mentioned prior art, provide the computing method of the low-permeability oil deposit water logging information that a kind of fluid is replaced, the method accurately obtains low-permeability oil deposit water logging information.
For achieving the above object, the computing method of the low-permeability oil deposit water logging information that fluid of the present invention is replaced comprise the following steps:
1) obtain the response characteristic of logging well before and after reservoir water logging in region, and choose lithology and physical property before and after water logging in the response characteristic of logging well before and after reservoir water logging from described region without the natural gamma GR of significant change and interval transit time AC logging trace;
2) well logging information of the model well of non-water logging in chosen area, then set up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging;
3) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate the model well to water logging in region, the resistivity t of original fluid contained by determining in the reservoir pore space of the model well of water logging in the reservoir pore space that obtains
1, and by the resistivity t of original fluid contained in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2contrast, obtain the resistivity t of contained original fluid in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2between change in resistance value Δ R
t;
4) by the formation testing information determination water percentage F of the model well of water logging in region
w, according to described water percentage F
wand step 2) the change in resistance value Δ R that obtains
tset up change in resistance value Δ R
tidentify the criteria for classifying of water flooded grade;
5) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate well to be evaluated in region in the reservoir pore space that obtains, obtain the resistivity of contained original fluid in the reservoir pore space of well to be evaluated in region, the resistivity of the well to be evaluated then resistivity of original fluid contained in the reservoir pore space of well to be evaluated in region and actual measurement obtained contrasts, change in resistance value Δ R between the resistivity of the well to be evaluated that the resistivity of original fluid contained by determining in the reservoir pore space of well to be evaluated in region and actual measurement obtain
s, then according to described change in resistance value Δ R
sand step 4) criteria for classifying of water flooded grade that obtains determines the water logging information of well to be evaluated in region.
The concrete operations of setting up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging are:
According to the well logging information of the model well of non-water logging based on the resistivity of original fluid contained in fuzzy clustering mathematics method establishment reservoir pore space and the funtcional relationship of natural gamma and interval transit time.
The concrete operations of setting up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging are:
The resistivity sample R in region to be measured is determined according to the well logging information of described model well
t, then the resistivity sample Rt in region to be measured is classified, and the resistivity sample R in region to be measured is set
tfuzzy diagnosis matrix U and central index vector S, then solve optimum fuzzy diagnosis matrix U by loop iteration
., optimal fuzzy clustering central index S
.and variable weight W
., then according to optimum fuzzy diagnosis matrix U
., optimal fuzzy clustering central index S
.and variable weight W
.determine the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space, wherein,
R
t ·=a×H+b;H=f(GRACU
·S
·W
·ρ)
In formula, R
t .for the resistivity curve data of original fluid contained in reservoir pore space, a and b is model coefficient, and f is the funtcional relationship mapped, GR and AC is natural gamma after normalization and interval transit time log data, 0.9≤ρ.
Adopt fuzzy clustering mathematics method Confirming model coefficient a and b, obtain a=0.1783, b=1.003.
Adopt fuzzy clustering mathematics method determination optimal fuzzy clustering central index S
.,
Adopt fuzzy clustering mathematics method determination variable weight W
., obtain W
.=(0.64250.3575);
ρ=0.9017。
The present invention has following beneficial effect:
The computing method of the low-permeability oil deposit water logging information that fluid of the present invention is replaced are in the process calculating low-permeability oil deposit water logging information, the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space is set up by the well logging information of the model well setting up non-water logging, then the resistivity of contained original fluid in reservoir pore space in region to be measured is calculated, the low-permeability oil deposit water logging information in region to be measured is obtained with the difference of the resistivity calculated again according to actual measurement, the present invention can meet the needs of actual production, through 120 mouthfuls of real well data process of oil field old secondary development, the low-permeability oil deposit water logging information conforms rate obtained reaches more than 83%, there is good using value.
Accompanying drawing explanation
Fig. 1 is model well resistivity sample R in embodiments of the invention one
tcumulative frequency distribution plan;
Fig. 2 is water percentage F in embodiments of the invention one
wwith change in resistance value Δ R
tchanging Pattern figure;
The reservoir resistivity changing value Δ R that Fig. 3 (a) is 60-63 layer in embodiments of the invention one
tschematic diagram;
The reservoir resistivity changing value Δ R that Fig. 3 (b) is 64-68 layer in embodiments of the invention one
tschematic diagram;
The reservoir resistivity changing value Δ R that Fig. 3 (c) is 56-59 layer in embodiments of the invention one
tschematic diagram.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail:
The computing method of the low-permeability oil deposit water logging information that fluid of the present invention is replaced comprise the following steps:
1) obtain the response characteristic of logging well before and after reservoir water logging in region, and choose lithology and physical property before and after water logging in the response characteristic of logging well before and after reservoir water logging from described region without the natural gamma GR of significant change and interval transit time AC logging trace;
2) well logging information of the model well of non-water logging in chosen area, then set up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging;
3) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate the model well to water logging in region, the resistivity t of original fluid contained by determining in the reservoir pore space of the model well of water logging in the reservoir pore space that obtains
1, and by the resistivity t of original fluid contained in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2contrast, obtain the resistivity t of contained original fluid in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2between change in resistance value Δ R
t;
4) by the formation testing information determination water percentage F of the model well of water logging in region
w, according to described water percentage F
wand step 2) the change in resistance value Δ R that obtains
tset up change in resistance value Δ R
tidentify the criteria for classifying of water flooded grade;
5) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate well to be evaluated in region in the reservoir pore space that obtains, obtain the resistivity of contained original fluid in the reservoir pore space of well to be evaluated in region, the resistivity of the well to be evaluated then resistivity of original fluid contained in the reservoir pore space of well to be evaluated in region and actual measurement obtained contrasts, change in resistance value Δ R between the resistivity of the well to be evaluated that the resistivity of original fluid contained by determining in the reservoir pore space of well to be evaluated in region and actual measurement obtain
s, then according to described change in resistance value Δ R
sand step 4) criteria for classifying of water flooded grade that obtains determines the water logging information of well to be evaluated in region.
Setting up in reservoir pore space the contained resistivity of original fluid according to the well logging information of the model well of non-water logging with the concrete operations of the funtcional relationship of natural gamma and interval transit time is: according to the well logging information of the model well of non-water logging based on the resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time contained by fuzzy clustering mathematics method establishment reservoir pore space.
The concrete operations of setting up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging are:
The resistivity sample R in region to be measured is determined according to the well logging information of described model well
t, then the resistivity sample R to region to be measured
tclassify, and the resistivity sample R in region to be measured is set
tfuzzy diagnosis matrix U and central index vector S, then solve optimum fuzzy diagnosis matrix U by loop iteration
., optimal fuzzy clustering central index S
.and variable weight W
., then according to optimum fuzzy diagnosis matrix U
., optimal fuzzy clustering central index S
.and variable weight W
.determine the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space, wherein,
R
t ·=a×H+b;H=f(GRACU
·S
·W
·ρ)
In formula, R
t .for the resistivity curve data of original fluid contained in reservoir pore space, a and b is model coefficient, and f is the funtcional relationship mapped, GR and AC is natural gamma after normalization and interval transit time log data, 0.9≤ρ.
Adopt fuzzy clustering mathematics method Confirming model coefficient a and b, obtain a=0.1783, b=1.003.
Adopt fuzzy clustering mathematics method determination optimal fuzzy clustering central index S
.,
Adopt fuzzy clustering mathematics method determination variable weight W
., obtain W
.=(0.64250.3575);
ρ=0.9017。
Embodiment one
According to region oil reservoir development background, by the comparative analysis to logging response character before and after the reservoir water logging of study area, before and after preferred water logging, lithology and physical property are without the natural gamma of significant change and interval transit time logging trace; According to the division limits of water percentage in " logging in water flooded layer datum processing specification (SY/T6178-2011) ", in conjunction with oil test data, choose the model well (F of representative non-water logging
w≤ 10% is non-water logging) well logging information, adopt the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in fuzzy clustering mathematics method establishment reservoir pore space, Fig. 1 is model well resistivity R
tthe cumulative frequency distribution plan of sample set, can be divided into 4 classes by resistivity sample set, and its funtcional relationship is: R
t .=a × H+b; H=f (GRACU
.s
.w
.ρ), in formula, R
t .for the resistivity curve data of original fluid contained in reservoir pore space; A and b is the coefficient of model, a=0.1783, b=1.003; F is the funtcional relationship mapped; GR and AC is natural gamma after normalization and interval transit time log data; S
.for optimal fuzzy clustering center matrix,
W
.=(0.64250.3575); ρ is related coefficient, ρ=0.9017, utilize the funtcional relationship of above-mentioned foundation, the model well described study area being chosen to representative water logging calculates, calculate the resistivity of contained original fluid in reservoir pore space, and with actual measurement resistivity contrasts, actual measurement resistivity is change in resistance value Δ R with calculating the difference of resistivity
t, change in resistance value Δ R
tcaused by fluid properties change in reservoir pore space; To change in resistance value Δ R
twith water percentage F
wanalyze, both present positive correlation, and meet One-place 2-th Order funtcional relationship, then in conjunction with water percentage F
wdivision limits, utilize change in resistance value Δ R
tobtain low-permeability oil deposit water logging information.When practical application, the criteria for classifying of water flooded grade is Δ R
t≤ 3.83 Ω .m are weak water logging, and 3.83 Ω .m< Δ Rt<51.34 Ω .m are middle water logging, Δ R
t>=51.34 Ω .m are strong water logging, and Fig. 2 is change in resistance value Δ R
twith water percentage F
wgraph of a relation.
In real data processing procedure, in inverting reservoir pore space, the resistivity curve of contained original fluid is realized by coding.Fig. 3 is the water flooded grade well logging interpretation result map replaced based on fluid: with reference to figure 3 (a), No. 60 floor based on the resistivity of original fluid contained in the reservoir pore space of fluid Shift Method inverting close to surveying resistivity, change in resistance value Δ R
tbe 1.46 Ω m, be less than 3.83 Ω m, according to the criteria for classifying of water flooded grade, well logging interpretation is weak water logging.Through Production development data verification, this well at 1435.0 ~ 1441.0m well section perforation, formation testing: oily 7.5t, water 4.05m
3, water percentage 35.06%; Go into operation: oily 5.84t, water 2.29m
3, water percentage 14.5%, formation testing conclusion is weak water logging, and well logging interpretation conforms to production is actual.With reference to figure 3 (b), in the reservoir pore space that No. 65 floor calculate based on fluid Shift Method, contained original fluid resistivity is less than actual measurement resistivity, change in resistance value Δ R
tbe 16.44 Ω m, between 3.83 and 51.34 Ω m, according to the criteria for classifying of water flooded grade, well logging interpretation is middle water logging.Through Production development data verification, this well at 1325 ~ 1328m well section perforation, formation testing: oily 10.08t, water 2.74m
3, water percentage 21.3%, goes into operation: oily 1.59t, water 2.56m
3, water percentage 61.6%, formation testing conclusion is middle water logging, and well logging interpretation conforms to production is actual.With reference to figure 3 (c), in the reservoir pore space that No. 58 floor calculate based on fluid Shift Method, contained original fluid resistivity is much smaller than actual measurement resistivity, change in resistance value Δ R
tbe 116.74 Ω m, be greater than 51.34 Ω m, according to the criteria for classifying of water flooded grade, well logging interpretation is for being strong water logging.Through Production development data verification, this well at 1642 ~ 1644m well section perforation, formation testing: oil bloom, water 12.6m
3, go into operation: oily 0.79t, water 4.95m
3, water percentage 86.2%, formation testing conclusion is strong water logging, and well logging interpretation meets produces reality.Through the process of 120 mouthfuls of real well data, and with Oil testing Comparative result, interpretation coincidence rate reaches 83%, demonstrates the validity of low-permeability oil deposit water logging information computing method of replacing based on fluid, has good effect.
The foregoing is only better enforcement figure of the present invention, not in order to limit the present invention, for those skilled in the art, within the spirit and principles in the present invention all, any amendment done and improvement etc., all should comprise in protection scope of the present invention.
Claims (7)
1. computing method for the low-permeability oil deposit water logging information of fluid replacement, is characterized in that, comprise the following steps:
1) obtain the response characteristic of logging well before and after reservoir water logging in region, and choose lithology and physical property before and after water logging in the response characteristic of logging well before and after reservoir water logging from described region without the natural gamma GR of significant change and interval transit time AC logging trace;
2) well logging information of the model well of non-water logging in chosen area, then set up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging;
3) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate the model well to water logging in region, the resistivity t of original fluid contained by determining in the reservoir pore space of the model well of water logging in the reservoir pore space that obtains
1, and by the resistivity t of original fluid contained in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2contrast, obtain the resistivity t of contained original fluid in the reservoir pore space of the model well of water logging
1the resistivity t of the model well of the water logging obtained with actual measurement
2between change in resistance value Δ R
t;
4) by the formation testing information determination water percentage F of the model well of water logging in region
w, according to described water percentage F
wand step 2) the change in resistance value Δ R that obtains
tset up change in resistance value Δ R
tidentify the criteria for classifying of water flooded grade;
5) step 2 is utilized) the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time calculate well to be evaluated in region in the reservoir pore space that obtains, obtain the resistivity of contained original fluid in the reservoir pore space of well to be evaluated in region, the resistivity of the well to be evaluated then resistivity of original fluid contained in the reservoir pore space of well to be evaluated in region and actual measurement obtained contrasts, change in resistance value Δ R between the resistivity of the well to be evaluated that the resistivity of original fluid contained by determining in the reservoir pore space of well to be evaluated in region and actual measurement obtain
s, then according to described change in resistance value Δ R
sand step 4) criteria for classifying of water flooded grade that obtains determines the water logging information of well to be evaluated in region.
2. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 1, it is characterized in that, the concrete operations of setting up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging are:
According to the well logging information of the model well of non-water logging based on the resistivity of original fluid contained in fuzzy clustering mathematics method establishment reservoir pore space and the funtcional relationship of natural gamma and interval transit time.
3. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 2, it is characterized in that, the concrete operations of setting up the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space according to the well logging information of the model well of non-water logging are:
The resistivity sample R in region to be measured is determined according to the well logging information of described model well
t, then the resistivity sample R to region to be measured
tclassify, and the resistivity sample R in region to be measured is set
tfuzzy diagnosis matrix U and central index vector S, then solve optimum fuzzy diagnosis matrix U by loop iteration
., optimal fuzzy clustering central index S
.and variable weight W
., then according to optimum fuzzy diagnosis matrix U
., optimal fuzzy clustering central index S
.and variable weight W
.determine the contained resistivity of original fluid and the funtcional relationship of natural gamma and interval transit time in reservoir pore space, wherein,
R
t ·=a×H+b;H=f(GRACU
·S
·W
·ρ)
In formula, R
t .for the resistivity curve data of original fluid contained in reservoir pore space, a and b is model coefficient, and f is the funtcional relationship mapped, GR and AC is natural gamma after normalization and interval transit time log data, 0.9≤ρ.
4. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 3, is characterized in that, adopt fuzzy clustering mathematics method Confirming model coefficient a and b, obtain a=0.1783, b=1.003.
5. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 3, is characterized in that, adopt fuzzy clustering mathematics method determination optimal fuzzy clustering central index S
.,
6. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 3, is characterized in that, adopt fuzzy clustering mathematics method determination variable weight W
., obtain W
.=(0.64250.3575).
7. the computing method of the low-permeability oil deposit water logging information of fluid replacement according to claim 3, is characterized in that, ρ=0.9017.
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CN108828675A (en) * | 2018-06-25 | 2018-11-16 | 桂林理工大学 | A kind of artificial swamp blocking region detection method for strengthening resistivity contrasts |
CN110017136A (en) * | 2019-03-14 | 2019-07-16 | 中国石油天然气集团有限公司 | A kind of Water Flooding Layer identification and producing water ratio prediction technique based on view water layer resistivity |
CN110344825A (en) * | 2019-06-28 | 2019-10-18 | 中国石油天然气股份有限公司 | Comprehensive judgment and identification method for low-pore low-permeability low-resistivity sandstone oil layer |
CN110792425A (en) * | 2019-11-21 | 2020-02-14 | 中国海洋石油集团有限公司 | Method for measuring water content of formation fluid |
CN111025409A (en) * | 2019-12-23 | 2020-04-17 | 中国石油大学(北京) | Flooded layer evaluation method and device and storage medium |
CN112360443A (en) * | 2020-08-19 | 2021-02-12 | 中国石油天然气股份有限公司 | Flooding level evaluation method based on rock resistance change rate and phase permeation coupling |
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