CN114016989B - Completion fracturing staged optimization method based on element logging interpretation data - Google Patents
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Abstract
The invention discloses a well completion fracturing staged optimization method based on element logging interpretation data, which comprises the following steps of: collecting interpretation data of element logging as a basic data set, wherein the basic data set comprises a plurality of parameters of shale gas well later fracturing; minimum assignment sigma using parameter i imin Sum maximum assignment sigma imax Calculating the relative fracturing index FR of each parameter i The method comprises the steps of carrying out a first treatment on the surface of the Calculating a comprehensive relative fracturing index FR of a plurality of parameters n : calculating the difference beta between the maximum value FRnmax 'of the input parameter FRn' and the input parameter FRn max : sequentially adding the difference beta max Dividing the steel into s grades, wherein the section length of each grade is Ls; sequentially searching a number Lsx which is between the minimum fracturing segment length Lmin and the maximum fracturing segment length Lmax and can be divided by the segment length Ls by using a remainder function: the fracturing index is segmented. The method is a well completion optimization technology based on element interpretation results and suitable for shale gas horizontal wells, can effectively improve the accuracy and effectiveness of horizontal well sectional design, and provides important support for oil testing geological design scheme and post-compaction evaluation.
Description
Technical Field
The invention relates to the technical field of shale gas development, in particular to a well completion fracturing staged optimization method based on element logging interpretation data.
Background
Over ten years, the exploration and development of domestic unconventional shale oil and gas resources are greatly advanced, a series of matched technologies for scale benefit development are formed, and a development mode of exploration and deployment integration, drilling and completion integration and production operation intensification is formed. Because the unconventional oil and gas reservoir has the characteristics of low holes and low permeability, the utilization of the horizontal well staged fracturing technology is an important means for realizing commercial development, wherein how to integrate multiple data sources according to logging or logging interpretation results is a key technical link in the implementation of overall staged optimization.
At present, after shale gas reservoirs are exploited in a large scale, in order to save cost, only part of well logging interpretation work is carried out on the same platform well, and how the well which is not subjected to logging interpretation further carries out horizontal well completion optimization design according to logging results is very important. In the conventional shale gas horizontal well completion design, the fracturing segmentation design is mainly based on logging interpretation results, so that the characteristics of heterogeneity and metamorphosis of horizontal segment reservoir parameters and completion parameters are difficult to consider more carefully, and the fracturing segmentation design is qualitative evaluation segmentation, so that the accuracy of later fracturing effect evaluation is affected.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a well completion fracturing staged optimization method with high precision based on element logging interpretation data.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the well completion fracturing staged optimization method based on the element logging interpretation data comprises the following steps:
s1: collecting interpretation data of element logging as a basic data set, wherein the basic data set comprises a plurality of parameters of shale gas well later fracturing;
s2: minimum assignment sigma using parameter i imin Sum maximum assignment sigma imax Calculating the relative fracturing index FR of each parameter i ：
S3: calculating a relative fracturing index FR for each parameter in the base data set i Obtaining comprehensive relative fracturing index indexes FR of a plurality of parameters in the basic data set:
wherein n is the number of parameters in the basic data set;
s4: calculating a comprehensive relative fracturing index FR of a plurality of parameters by utilizing the comprehensive relative fracturing index FR n ：
S5: comprehensive relative fracturing index FR using weighting function n Smoothing to obtain input parameter FR n '；
S6: calculate input parameter FR n Maximum value FR of nmax ' and input parameter FR n ' difference beta max ：
β max ＝FR nmax '-FR n '
S7: sequentially adding the difference beta max Is divided into s grades, and the segment length of each grade is L s ；
S8: sequentially searching the minimum fracturing segment length L by using remainder function min To maximum fracture length L max Can be divided into sections of L s Number of integer divisors L sx ：
S9: judging whether the remainder is equal to 0, ifThe fracturing index is segmented into: (D) max -L ix )～(D max )，(D max -2L ix )～(D max -L ix )，···，(D max -sL ix )～(D max -(s-1)L ix ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein D is max The bottom depth of the logging data;
s10: if it isReturning to step S8, the available segment length L is found again s Number of integer divisors L sx 。
Further, the plurality of shale gas well later fracturing parameters comprise positive parameters and negative parameters, wherein the positive parameters are parameters with positive effects on shale gas well later fracturing, and the larger the positive parameters are, the better the positive parameters are; the negative parameters are parameters with negative effects on the later fracturing of the shale gas well and serve as negative parameters; the better the negative going parameter.
Further, step S7 includes:
s71: sequentially adding the difference beta max The method comprises the steps of dividing the system into s grades, wherein the s grades sequentially comprise: first stageSecond stageS. level->
S72: calculating the length L of each grade segment s ：
Further, relative fracturing index FR i The calculation method comprises the following steps:
wherein W is i As the weight coefficient of parameter I, I i p2 is the percentile of 2% of parameter I i p98 is the percentile of 98% of parameter i.
The beneficial effects of the invention are as follows: the method is a well completion optimization technology based on element interpretation results and suitable for shale gas horizontal wells, can effectively improve the accuracy and effectiveness of horizontal well sectional design, and provides important support for oil testing geological design scheme and post-compaction evaluation. The invention can integrate data from multiple aspects such as drilling data, logging, ground logging, petrophysical and geomechanical interpretation, core, cuttings analysis, production data and the like, reduce the variation of reservoir heterogeneity in the section, and provide important support for oil testing geological design and post-pressure evaluation.
Drawings
FIG. 1 is a flow chart of a completion fracture staging optimization method based on elemental log interpretation data.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
As shown in fig. 1, the well completion fracturing staged optimization method based on the element logging interpretation data of the scheme comprises the following steps:
s1: collecting interpretation data of element logging as a basic data set, wherein the basic data set comprises a plurality of parameters of shale gas well later fracturing; the shale gas well later fracturing parameters comprise positive parameters and negative parameters, wherein the positive parameters are parameters with positive effects on shale gas well later fracturing, and the larger the positive parameters are, the better the positive parameters are; such as porosity, TOC, total gas content, total hydrocarbon content, methane content, brittle mineral content, young's modulus, natural fracture density, etc. The negative parameters are parameters with negative effects on the later fracturing of the shale gas well and serve as negative parameters; the better the negative parameters are; for example: density, water saturation, formation fracture pressure, minimum level principal stress, poisson's ratio, etc.
S2: minimum assignment sigma using parameter i imin Sum maximum assignment sigma imax Calculating the relative fracturing index FR of each parameter i The method for calculating the relative fracturing index FRi comprises the following steps:
wherein W is i As the weight coefficient of parameter I, I i p2 is the percentile of 2% of parameter I i p98 is the percentile of 98% of parameter i.
S3: calculating a relative fracturing index FR for each parameter in the base data set i Obtaining comprehensive relative fracturing index indexes FR of a plurality of parameters in the basic data set:
wherein n is the number of parameters in the basic data set;
s4: calculating a comprehensive relative fracturing index FR of a plurality of parameters by utilizing the comprehensive relative fracturing index FR n ：
S5: comprehensive relative fracturing index FR using weighting function n Smoothing to obtain input parameter FR n '；
S6: calculate input parameter FR n Maximum value FR of nmax ' and input parameter FR n ' difference beta max ：
β max ＝FR nmax '-FR n '
S7: sequentially adding the difference beta max Is divided into s grades, and the segment length of each grade is L s The method comprises the steps of carrying out a first treatment on the surface of the Comprising the following steps:
s71: sequentially adding the difference beta max The method comprises the steps of dividing the system into s grades, wherein the s grades sequentially comprise: first stageSecond stageS. level->
S72: calculating the length L of each grade segment s ：
S8: sequentially searching the minimum fracturing segment length L by using remainder function min To maximum fracture length L max Can be divided into sections of L s Number of integer divisors L sx ：
S9: judging whether the remainder is equal to 0, ifThe fracturing index is segmented into: (D) max -L ix )～(D max )，(D max -2L ix )～(D max -L ix )，···，(D max -sL ix )～(D max -(s-1)L ix ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein D is max The bottom depth of the logging data;
s10: if it isReturning to step S8, the available segment length L is found again s Number of integer divisors L sx 。
The method is a well completion optimization technology based on element interpretation results and suitable for shale gas horizontal wells, can effectively improve the accuracy and effectiveness of horizontal well sectional design, and provides important support for oil testing geological design scheme and post-compaction evaluation. The invention can integrate data from multiple aspects such as drilling data, logging, ground logging, petrophysical and geomechanical interpretation, core, cuttings analysis, production data and the like, reduce the variation of reservoir heterogeneity in the section, and provide important support for oil testing geological design and post-pressure evaluation.
Claims (4)
1. A well completion fracturing staged optimization method based on element logging interpretation data is characterized by comprising the following steps of:
s1: collecting interpretation data of element logging as a basic data set, wherein the basic data set comprises a plurality of parameters of shale gas well later fracturing;
s2: minimum assignment sigma using parameter i imin Sum maximum assignment sigma imax Calculating the relative fracturing index FR of each parameter i ：
S3: calculating a relative fracturing index FR for each parameter in the base data set i Obtaining comprehensive relative fracturing index indexes FR of a plurality of parameters in the basic data set:
wherein n is the number of parameters in the basic data set;
s4: calculating a comprehensive relative fracturing index FR of a plurality of parameters by utilizing the comprehensive relative fracturing index FR n ：
S5: comprehensive relative fracturing index FR using weighting function n Smoothing to obtain input parameter FR n '；
S6: calculate input parameter FR n Maximum value FR of nmax ' and input parameter FR n ' difference beta max ：
β max ＝FR nmax '-FR n '
S7: sequentially adding the difference beta max Is divided into s grades, and the segment length of each grade is L s ；
S8: sequentially searching the minimum fracturing segment length L by using remainder function min To maximum fracture length L max Can be divided into sections of L s Number of integer divisors L sx ：
S9: judging whether the remainder is equal to 0, ifThe fracturing index is segmented into: (D) max -L ix )～(D max )，(D max -2L ix )～(D max -L ix )，···，(D max -sL ix )～(D max -(s-1)L ix ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein D is max The bottom depth of the logging data;
s10: if it isReturning to step S8, the available segment length L is found again s Number of integer divisors L sx 。
2. The staged optimization method for well completion and fracturing based on element logging interpretation data according to claim 1, wherein the plurality of shale gas well post-fracturing parameters comprise positive parameters and negative parameters, the positive parameters are parameters with positive effects on shale gas well post-fracturing, and the larger the positive parameters are, the better the positive parameters are; the negative parameters are parameters with negative effects on the later fracturing of the shale gas well and serve as negative parameters; the better the negative going parameter.
3. The method for staged optimization of completion fracturing based on elemental log interpretation data of claim 1, wherein step S7 comprises:
s71: sequentially adding the difference beta max The method comprises the steps of dividing the system into s grades, wherein the s grades sequentially comprise: first stageSecond stageS. level->
S72: calculating the length L of each grade segment s ：
4. The method of staged optimization of completion fracturing based on elemental log interpretation data of claim 1, wherein the relative fracturing index FR i The calculation method comprises the following steps:
wherein W is i As the weight coefficient of parameter I, I i p2 is the percentile of 2% of parameter I i p98 is the percentile of 98% of parameter i.
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