CN105512749A - Quantitative prediction method for water production rate of water flooded layer - Google Patents
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Abstract
The invention discloses a quantitative prediction method for a water production rate of a water flooded layer. The method comprises: same target stratums of existing wells, water production rate data at different time points, and well coordinate data in a block where a to-be-predicated new well is located are collected; a group of water production rate distribution graphs of the same target stratums at different time points are generated by software; fitting is carried out based on a series of numerical values of the to-be-predicated new well in the group of water production rate distribution graphs to obtain a water production rate prediction model; and a water production rate of the to-be-predicated new well is calculated based on the prediction well. The practice has proved that compared with the previous traditional logging processing method, the provided method enables the accuracy to be improved by about 20%.
Description
Technical field
The invention belongs to field of oil development, be specifically related to the quantitative forecasting technique in a kind of water flooding process, submerged degree of oil reservoir analyzed.
Background technology
At present, well logging means are mainly relied on for the predicting and appraising of Water Flooding Layer in oil field, the predicting and appraising method of main employing carries out the logging trace qualitative analysis of individual well, to target well, whether water logging qualitatively judges the general Changing Pattern of logging trace of the Water Flooding Layer that foundation was summed up in the past, utilizes the experimental formula of theoretical model or foundation to calculate some quantitative parameters simultaneously and differentiates water logging and water flooded grade.
But from the effect of real predicting and appraising Water Flooding Layer, prior art comments the accuracy rate of method evaluation reservoir water flooding lower, according to statistics, the well logging interpretation accuracy rate of Water Flooding Layer is about 60%, and accuracy rate is lower to be caused primarily of following two aspect factors:
1, logging trace is numerous by the influence factor outside Water Flooding Layer information, and qualitative resolution water logging effective information is difficult:
Logging trace is a kind of appearance form of electronic signal, and electronic signal can be subject to many factors interference in acquisition process, comprises instrument signal collection, wellbore conditions, mud property, stratum difference and injected water salinity etc.The interference of these factors makes logging trace not only react reservoir water flooding change, but the combined reaction of many factors, even can cover the impact of water logging on logging trace, therefore at this complex condition, to differentiate and to extract the variation characteristic difficulty of water logging on logging trace larger, simultaneously when qualitative discrimination, often depend on practical experience and the knowledge background of explanation personnel individual, easily cause the consequence that different people analysis conclusion differs greatly;
2, logging in water flooded layer quantitative interpretation model relates to that parameter is many, complicated the causing of conversion process explain that conclusion error is larger:
Well logging means are utilized quantitatively to calculate the key parameters such as Water Flooding Layer producing water ratio, it is the experimental formula that explanation personnel set up coincidence theory basis, and mostly need to go out producing water ratio by the repeatedly conversion indirect calculation of several parameter, therefore the accuracy of interpretation model itself and the conversion process of multiparameter all can bring the impact of many unknowns, finally can have influence on the calculating accuracy rate of producing water ratio.
Summary of the invention
The object of the invention is to overcome the defect that in above-mentioned prior art, Water Flooding Layer predictablity rate is lower, technical scheme of the present invention is to provide a kind of water-flooded layer water productivity quantitative forecasting method.
For solving the problems of the technologies described above, the technical solution used in the present invention is as follows:
A kind of water-flooded layer water productivity quantitative forecasting method, comprises the following steps that order connects:
Steps A, collection comprise the existing identical zone of interest of well, the producing water ratio data of different time points and well location coordinate data in the block of Xin Jing place to be predicted;
Step B, the producing water ratio data of the different time points of steps A gained and well location coordinate are loaded into possess the software simulating that isoline becomes figure function, obtain the producing water ratio isogram of identical zone of interest, different time points, the producing water ratio isogram of these different time points is combined, had both defined zone of interest producing water ratio space-time comparison diagram;
Step C, well location coordinate according to new well to be predicted, determine new well to be predicted position in producing water ratio space-time comparison diagram, and then obtain one group of producing water ratio value of new well to be predicted different time points on producing water ratio space-time comparison diagram;
Step D, obtain the producing water ratio Fw of Xin Jing present position to be predicted zone of interest and the Relationship Prediction model formation of time t according to the producing water ratio value matching of the to be predicted new well of step C gained;
Step e, the forecast model formulae discovery of step D gained is utilized to obtain new well zone of interest producing water ratio Fw value to be predicted according to the timing node of new well present stage to be predicted.
Above-mentioned purpose layer refers to the layer residing for new well to be predicted, and identical zone of interest refers to new well location to be predicted in same layer.
In above-mentioned steps D, the Relationship Prediction model formation type of producing water ratio Fw and time t is not limit, and can be once, secondary, three inferior various forms, specifically depends on fitting result.
In above-mentioned steps A of the present invention, the choosing method principle of different time points is: in block zone of interest waterflooding time total span, according to the data degree grasped, preferred zone of interest has several time points of well producing water ratio data relative abundance, and the time point that last time point is preferably nearest apart from new well to be predicted; The producing water ratio collected and well location coordinate data are: the existing well producing water ratio of (each well when block zone of interest waterflooding in the time period up to now) zone of interest and coordinate data over the years in the block comprising new well to be predicted.
Preferably, according in step D, the producing water ratio Fw of Xin Jing present position to be predicted zone of interest that matching obtains and the Relationship Prediction model formation of time t are Fw=a
2t+bt+c, wherein a, b, c is the constant that formula fitting goes out.
Above-mentioned time t can in units of year, the moon or day equal time, and specifically determine according to the time point of collected existing well, commonly use as the moon, if during the moon, time t refers to the quantity of when initial time month to predicted time month " moon ".
In above-mentioned steps B, Become the picture software is have the software that Kriging regression algorithm realization isoline becomes figure function, can preferred Gxplorer or sufer software.
The producing water ratio Fw size that the division of water logging grade then calculates according to above-mentioned model divides, and when producing water ratio is less than 10%, is oil reservoir; When producing water ratio is 10% ~ 40%, it is weak Water Flooding Layer; When producing water ratio is 40% ~ 80%, it is middle Water Flooding Layer; When producing water ratio is greater than 80%, it is high Water Flooding Layer.
Feature of the present invention is:
A. resolving ideas embodies broad perspectives: resolving ideas of the present invention goes analysis purpose layer water logging distribution situation whole from the block integral angle residing for new well to be predicted, make full use of the water logging data of existing well, the basis of fully having grasped block integral water logging situation is predicted, avoids that traditional logging evaluation Water Flooding Layer mode only goes to differentiate water logging problem from individual well angle and the broad perspectives that easily causes analyzes not enough problem; B. processing mode embodies dynamic: this method is by obtaining the Changing Pattern of zone of interest water logging in the plane to the statistical study of identical zone of interest, different time points producing water ratio, the water logging data Modling model of recycling different time points predicts the zone of interest water logging situation of new well, and this mode embodies the dynamic process of Water Flooding Layer time to time change; C. prediction mode, method have substantivity: whole work of the present invention all launches around this core parameter of producing water ratio, set up in link at key forecast model and directly utilize producing water ratio data, also directly producing water ratio is embodied on predicting the outcome, whole method flow avoids other nuisance parameters and quotes and the conversion of too much processing links, therefore at utmost avoids error that subjective factor causes to the impact predicted the outcome.
The essence of water logging is overall, a dynamic things change procedure, and more meet the essence of Water Flooding Layer from the inventive method of this angle employing, its objectivity evaluated and accuracy are improved naturally.
A kind of water-flooded layer water productivity quantitative forecasting method of the present invention, with having entirety, dynamic thinking and method evaluation Water Flooding Layer, more realistic, its evaluate objectivity and accuracy rate greatly improve, this method prove in practice accuracy rate more in the past traditional treatment method can improve about 20%.
Accompanying drawing explanation
Fig. 1 is E in the embodiment of the present invention 1
1f
1 1interval 1 substratum 97 years-03 year-05 year-07 year-09 year producing water ratio space-time comparison diagram;
Fig. 2 is E residing for A well 1 substratum in the embodiment of the present invention 1
1f
1 1producing water ratio forecast model on series of strata position;
Fig. 3 is E in the embodiment of the present invention 2
1f
1 2interval 1 substratum 97 years-03 year-05 year producing water ratio space-time comparison diagram;
Fig. 4 is E residing for B well 1 substratum in the embodiment of the present invention 2
1f
1 2producing water ratio forecast model on series of strata position;
Fig. 5 is E in the embodiment of the present invention 3
1f
2 3interval 1 substratum 97 years-03 year-05 year-07 year producing water ratio space-time comparison diagram;
Fig. 6 is E residing for C well 1 substratum in the embodiment of the present invention 3
1f
2 3producing water ratio forecast model on series of strata position;
Fig. 7 is the Forecasting Methodology process flow diagram of high accuracy Water Flooding Layer producing water ratio of the present invention.
Embodiment
In order to understand the present invention better, illustrate content of the present invention further below in conjunction with embodiment, but content of the present invention is not only confined to the following examples.
Following Fig. 1,3, lines in 5 figure are producing water ratio isoline, in figure, pentagram represents new well to be predicted and is in position in figure, and the delimitation of water flooded grade take producing water ratio as foundation.
Embodiment 1:A well
A well (representing with pentagram in Fig. 1) is positioned at the northern slope of depression, and be the oil recovery interspaced well that completes in October, 2009, exploiting main layer is E
1f
1 1series of strata 1 substratum.
Step one: generate E
1f
1 1series of strata 1 substratum producing water ratio space-time comparison diagram: according to this block E
1f
1 1series of strata 1 substratum has producing water ratio data cases, select in Dec, 97 of producing water ratio data relative abundance, in Dec, 03, in Dec, 05, in Dec, 07 and 09 year May 5 timing nodes well coordinate and producing water ratio data, isoline is utilized to become figure functional software to generate different time points producing water ratio distribution plan (note: Become the picture software is that the isoline with Kriging regression algorithm becomes figure functional software, sufer software), the producing water ratio figure of comprehensive different time points had both been E
1f
1 1series of strata 1 substratum producing water ratio space-time comparison diagram, as shown in Figure 1.
Step 2: set up E
1f
1 1series of strata 1 substratum producing water ratio forecast model: from E
1f
1 1on series of strata 1 substratum space-time comparison diagram, coordinate position (in figure pentagram present position) residing for A well obtains producing water ratio (Fw) data (in Dec, 97 producing water ratio (Fw)=0%; In Dec, 03 producing water ratio (Fw)=25%; In Dec, 05 producing water ratio (Fw)=43%; In Dec, 07 producing water ratio (Fw)=51%; 09 year 05 month producing water ratio (Fw)=58%), according to data fitting A well E
1f
1 1series of strata 1 substratum producing water ratio forecast model, as shown in Figure 2.
Step 3: calculate A well E
1f
1 1series of strata 1 substratum producing water ratio: according to Fig. 2 forecast model (y=0.0022x
2+ 0.407x-0.5654), A well E
1f
1 1series of strata 1 substratum is when in October, 09, and water filling adds up month to reach 142 months, calculates E by forecast model
1f
1 1the comprehensive producing water ratio of series of strata 1 substratum is 61.8%, is middle Water Flooding Layer.
Conclusion is verified: this well perforation at the beginning of in November, 2009 is gone into operation 1 substratum, and actual producing water ratio is 59.8%, belongs to middle Water Flooding Layer, and it is 61.8% that above-mentioned accuracy method predicts the outcome, and predicting the outcome, to exploit result kiss property with reality fine.
Embodiment 2:B well
B well (representing with pentagram in Fig. 3) is positioned at the middle part of structure, is to develop E flatly
1f
1 2the producing well of series of strata 1 substratum, finishing drilling at the beginning of 2007 1 month.
Step one: generate E
1f
1 2series of strata 1 substratum producing water ratio space-time comparison diagram: according to this block E
1f
1 2series of strata 1 substratum has producing water ratio data cases, select in Dec, 97 of producing water ratio data relative abundance, in Dec, 03,05 year Dec 3 timing nodes well coordinate and producing water ratio data, isoline is utilized to become figure functional software to generate different time points producing water ratio distribution plan (note: Become the picture software is that the isoline with Kriging regression algorithm becomes figure functional software, Gxplorer software), the producing water ratio figure of comprehensive different time points had both been E
1f
1 2series of strata 1 substratum producing water ratio space-time comparison diagram, as shown in Figure 3.
Step 2: set up E
1f
1 2series of strata 1 substratum producing water ratio forecast model: from E
1f
1 2on series of strata 1 substratum space-time comparison diagram, coordinate position (in figure pentagram present position) residing for B well obtains producing water ratio (Fw) data (in Dec, 97 producing water ratio (Fw)=2%; In Dec, 03 producing water ratio (Fw)=3%; In Dec, 05 producing water ratio (Fw)=3%), according to data fitting B well E
1f
1 2series of strata 1 substratum producing water ratio forecast model, as shown in Figure 4.
Step 3: calculate B well E
1f
1 2series of strata 1 substratum producing water ratio: the forecast model (y=-0.0001x of Fig. 4 matching
2+ 0.0243x+2) calculate B well E
1f
1 2series of strata 1 substratum is when in January, 07, and water filling adds up month to reach 109 months, and calculating producing water ratio by forecast model is 3.5%, is oil reservoir, and illustrating that this well 1 substratum is not by water logging, is oil reservoir.
Conclusion is verified: this well in January, 2007 perforation to go into operation 1 substratum, actual producing water ratio is 4%, is oil reservoir.It is 3.5% that above-mentioned accuracy method predicts the outcome, predict the outcome and exploit result kiss property with reality and (do not adopt methods described herein very well, but the conclusion adopting the mode of traditional well logging interpretation in the past to obtain separately differentiates that in this section of series of strata, reservoir is Water Flooding Layer), the practicality of sufficient proof this method and reliability.
Embodiment 3:C well
C well (representing with pentagram in Fig. 5) is positioned at the middle part of structure, is to develop E flatly
1f
2 3the producing well of series of strata 1 substratum, in finishing drilling in July, 2008.
Step one: generate E
1f
2 3series of strata 1 substratum producing water ratio space-time comparison diagram: according to this block E
1f
2 3series of strata 1 substratum has producing water ratio data cases, select in Dec, 97 of producing water ratio data relative abundance, in Dec, 03, in Dec, 05 and 07 year Dec 4 timing nodes well coordinate and producing water ratio data, isoline is utilized to become figure functional software to generate different time points producing water ratio distribution plan (note: Become the picture software is that the isoline with Kriging regression algorithm becomes figure functional software, sufer software), the producing water ratio figure of comprehensive different time points had both been E
1f
2 3series of strata 1 substratum producing water ratio space-time comparison diagram, as shown in Figure 5.
Step 2: set up E
1f
2 3series of strata 1 substratum producing water ratio increases progressively relational model: from E
1f
2 3on series of strata 1 substratum space-time comparison diagram, coordinate position (in figure pentagram present position) residing for C well obtains producing water ratio (Fw) data (in Dec, 97 producing water ratio (Fw)=0%; To in Dec, 03 producing water ratio (Fw)=27%; In Dec, 05 producing water ratio (Fw)=43%; In Dec, 07 producing water ratio (Fw)=55%; ), according to data fitting C well E
1f
2 3series of strata 1 substratum producing water ratio forecast model, as shown in Figure 6.
Step 3: calculate C well E
1f
2 3series of strata 1 substratum producing water ratio: according to Fig. 6 forecast model (y=0.0015x
2+ 0.2866x-0.1243), C well E
1f
2 3series of strata 1 substratum is when in July, 08, and water filling adds up month to reach 127 months, calculates E by forecast model
1f
2 3the comprehensive producing water ratio of series of strata 1 substratum is 60.5%, is middle Water Flooding Layer.
Conclusion is verified: this well in July, 2008 perforation to go into operation 1 substratum, actual producing water ratio is 62.4%, is middle Water Flooding Layer.It is 60.5% that above-mentioned accuracy method predicts the outcome, predict the outcome and exploit result kiss property with reality and (do not adopt methods described herein very well, but adopt the conclusion that the logging trace of traditional well logging interpretation in the past qualitatively judges and quantitative interpretation obtains to be oil reservoir separately, result grave fault is exploited with reality), the practicality of sufficient proof this method and reliability.
Table 1 water flooded grade confirmed standard reference table
| Water logging grade | Water percentage Fw (%) |
| Oil reservoir (non-water logging) | F w≤10％ |
| Weak Water Flooding Layer | 10％<F w≤40％ |
| Middle Water Flooding Layer | 40％<F w≤80％ |
| High Water Flooding Layer | F w>80％ |
Table 2 becomes figure desired data base data table for Fig. 1
Table 3 becomes figure desired data base data table for Fig. 3
Table 4 becomes figure desired data base data table for Fig. 5
Claims (5)
1. a water-flooded layer water productivity quantitative forecasting method, is characterized in that: comprise the following steps that order connects:
Steps A, collection comprise the existing identical zone of interest of well, the producing water ratio data of different time points and well location coordinate data in the block of Xin Jing place to be predicted;
Step B, the producing water ratio data of the different time points of steps A gained and well location coordinate are loaded into possess the software simulating that isoline becomes figure function, obtain the producing water ratio isogram of identical zone of interest, different time points, the producing water ratio isogram of these different time points is combined, had both defined zone of interest producing water ratio space-time comparison diagram;
Step C, well location coordinate according to new well to be predicted, determine new well to be predicted position in producing water ratio space-time comparison diagram, and then obtain one group of producing water ratio value of new well to be predicted different time points on producing water ratio space-time comparison diagram;
Step D, obtain the producing water ratio Fw of Xin Jing present position to be predicted zone of interest and the Relationship Prediction model formation of time t according to the producing water ratio value matching of the to be predicted new well of step C gained;
Step e, the forecast model formulae discovery of step D gained is utilized to obtain new well zone of interest producing water ratio Fw value to be predicted according to the timing node of new well present stage to be predicted.
2. a kind of water-flooded layer water productivity quantitative forecasting method as claimed in claim 1, is characterized in that: according in step D, and the producing water ratio Fw of Xin Jing present position to be predicted zone of interest that matching obtains and the Relationship Prediction model formation of time t are Fw=a
2t+bt+c, wherein a, b, c is the constant that formula fitting goes out.
3. a kind of water-flooded layer water productivity quantitative forecasting method as claimed in claim 1 or 2, is characterized in that: when producing water ratio Fw is less than 10%, is oil reservoir; When producing water ratio Fw is 10% ~ 40%, it is weak Water Flooding Layer; When producing water ratio Fw is 40% ~ 80%, it is middle Water Flooding Layer; When producing water ratio Fw is greater than 80%, it is high Water Flooding Layer.
4. a kind of water-flooded layer water productivity quantitative forecasting method as claimed in claim 1 or 2, is characterized in that: possess isoline in step B and become the software of figure function to be the isoline Become the picture software possessing Kriging regression algorithm function.
5. a kind of water-flooded layer water productivity quantitative forecasting method as claimed in claim 4, is characterized in that: possess isoline in step B and become the software of figure function to be sufer software or gxplorer software.
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| CN101942994A (en) * | 2010-09-16 | 2011-01-12 | 中国石油天然气股份有限公司 | Quantitative prediction method and system for water yield of flooded layer |
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Application publication date: 20160420 |