CN105604544A - Indoor evaluation method for reservoir water sensitivity - Google Patents
Indoor evaluation method for reservoir water sensitivity Download PDFInfo
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- CN105604544A CN105604544A CN201410643515.3A CN201410643515A CN105604544A CN 105604544 A CN105604544 A CN 105604544A CN 201410643515 A CN201410643515 A CN 201410643515A CN 105604544 A CN105604544 A CN 105604544A
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Abstract
The invention provides an indoor evaluation method for reservoir water sensitivity, the method comprising the steps of: firstly, based on core analysis data, establishing a well logging secondary interpretation model of the water sensitivity index and a plurality of parameters by using a multiple linear regression method; secondly, performing well logging secondary interpretation of porosity; thirdly, performing well logging secondary interpretation of permeability; fourthly, performing well logging interpretation of shale content; fifthly, putting the parameters of secondary interpretation in the second-fourth steps in the well logging secondary interpretation model of the first step for whole-region vertical and transversal prediction of the water sensitivity index. The indoor evaluation method for reservoir water sensitivity solves the problem that the evaluation of water sensitivity cannot be performed in regions without cored wells or with fewer cored wells and the vertical and transversal change rules of reservoirs can be researched by using the well logging method.
Description
Technical field
The present invention relates to the evaluating reservoir in oil exploration and development field, specially refer to the quick (speed of reservoir sensitivity evaluation fiveQuick, water-sensitive, acid-sensitive, salt is quick, alkali is quick) in water sensitivity method.
Background technology
Oil layer protection has become important measures of storing up in chronicity, strategic task and a volume increase in oil field at present.Reservoir sensitivity has also carried out mechanism research and in-depth, and laboratory experiment utilizes the oleic permeability under irreducible water condition to survey simultaneouslyFixed reality, the characterize reservoir percolation ability accurately of approaching. But be subject to the water-sensitive sample that core hole data is few, foundation is limitedCannot accurate description reservoir water sensitivity vertical, horizontal Changing Pattern, can not serve as a kind of water sensitivity evaluation method of routine. For this reasonWe have invented a kind of new reservoir water sensitivity indoor evaluation method, have solved above technical problem.
Summary of the invention
The object of this invention is to provide one and utilize well-log information scale water sensitive index, comment thereby reservoir is carried out to water sensitivityThe method of valency.
Object of the present invention can be achieved by the following technical measures: reservoir water sensitivity indoor evaluation method, this reservoir waterSensitiveness indoor evaluation method comprises: step 1, utilize core analyzing data, and adopt multiple linear regression analysis method to set up water-sensitiveThe logging interpretation models of index and multiple parameters; Step 2, well logging second interpretation porosity; Step 3, well logging secondaryExplain permeability; Step 4, well log interpretation shale content; And step 5, by the parameter substitution of second interpretation in step 2-4The logging interpretation models of step 1, carries out the vertical lateral prediction of whole district's water sensitive index.
Object of the present invention also can be achieved by the following technical measures:
In step 1, utilize log data, the water sensitive index I of calculation block diverse locationW, the prediction whole district is in length and breadth to water-sensitivePerception.
In step 1, by water sensitive index IWBe divided into extremely strong water-sensitive, strong water-sensitive, middle isogonic according to large young pathbreaker's water-sensitive intensity of valueStrong water-sensitive, medium water-sensitive on the weak side, weak water-sensitive and without water-sensitive, work as IWWithin≤5 o'clock, be without water-sensitive, as 5 < IWWithin≤30 o'clock, be weak water-sensitive,As 30 < IWWithin≤50 o'clock, be medium water-sensitive on the weak side, as 50 < IWWithin≤70 o'clock, be the strong water-sensitive of middle isogonic, as 70 < IWWithin≤90 o'clock, be strong water-sensitive,Work as IW> 90 o'clock be extremely strong water-sensitive.
In step 1, the logging interpretation models of foundation is:
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64。
In formula:
IWFor water sensitive index; φ is porosity, %; K is permeability, mD; Zwc is comprehensive physical parameter, Zwc=SQT(K/ φ); Vsh is shale content, %; RAllFor pore throat radius average, μ m; RInFor pore throat median radius, μ m.
In step 1, parameter porosity φ, permeability K, comprehensive physical property parameter Z wc, Zwc=SQT (K/ φ), shale containAmount Vsh is obtained by log data, pore throat radius average RAll, pore throat median radius RInObtained by experimental data.
In step 2, the formula of well logging second interpretation porosity is:
φ＝-0.132×AC+171.98×LOG(AC)+105.986×LOG(Depth)-693.09
In formula, φ: porosity, %; AC: interval transit time after proofreading and correct, ms/m; Depth: the degree of depth, m.
In step 3, the formula of well logging second interpretation permeability is:
K＝1031.55578×LOG(Depth)-0.1436×φ+11.023635×LOG(φ)-1.039×LOG(GR)-105.48857
In formula, K: permeability, mD; φ: porosity, %; Depth: the degree of depth, m; GR: natural gamma, API.
In step 4, the computing formula that is called as natural gamma relative value or shaliness index SHI is:
SHI＝(GR-GRmin)/(GRmax-GRmin)
Wherein, GR: natural gamma, API, pure shale be labeled as GRmax, clean sandstone be labeled as GRmin；
The computing formula of well log interpretation shale content is:
Vsh＝(2SHI×GCUR-1)/(2GCUR-1)
In formula, Vsh, well log interpretation shale content, %; CGUR is an empirical of matching rock core information, by experienceOr matching rock core information is determined.
In step 5, logging interpretation models is:
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64
In formula: φ is well logging second interpretation porosity, %; K is well logging second interpretation permeability, mD; Zwc is comprehensive physical propertyParameter, Zwc=SQT (K/ φ); Vsh is well log interpretation shale content, %; Pore throat radius average RAll, pore throat median radius RInReplace with core hole mean value.
This reservoir water sensitivity indoor evaluation method, provides a kind of prediction block in length and breadth to the method for water sensitive degree, profitWith core analysis chemical examination data employing multiple linear regression water sensitive second interpretation formula, predict and do not core or coreDo not do the block water sensitivity of water-sensitive experiment. Adopt water sensitive index second interpretation formula to do water sensitivity and evaluate this reservoir waterIf sensitiveness indoor evaluation method also comprises does not have the porosity of analytical test, permeability, shale content experimental data,Porosity, permeability, these parameters of shale content also can contain with porosity, permeability, the shale of well logging second interpretationAmount. Generally, pore throat average, median radius need to have analytical test data. The method can be effectively vertical by reservoirLaterally water sensitivity carries out meticulous division, solve because core hole is few, or cannot differentiate without core hole block water sensitivityProblem, has realized and has utilized the vertical and horizontal Changing Pattern research of logging method Study In Reservoir.
Brief description of the drawings
Fig. 1 is the flow chart of a specific embodiment of reservoir water sensitivity indoor evaluation method of the present invention;
Fig. 2 is in a specific embodiment of the present invention, log well second interpretation water sensitive index and experiment water sensitive index graph of a relation.
Detailed description of the invention
For above and other object of the present invention, feature and advantage can be become apparent, cited below particularly go out preferred embodiment,And coordinate appended graphicly, be described in detail below.
The principal element that affects water sensitivity power has shale content, permeability and pore structure. Research shows water sensitivity powerBe good positive correlation with shale content, shale content is higher, and water sensitivity is stronger. Water sensitive index and permeability are negativeRelevant, the higher water sensitivity of permeability is more weak. Reservoir water sensitivity and pore structure have good correlation, hole knotStructure the present invention has adopted pore throat median radius and two major parameters of pore throat radius average, with pore throat median radius, pore throat halfThe increase water sensitive index of footpath average is obvious downward trend, and coefficient correlation is 0.98. Study above basic on, IInvented a kind of new reservoir water sensitivity indoor evaluation method, set up water sensitive index and porosity φ (%), infiltrationRate K (mD), comprehensive physical property parameter Z wc, Zwc=SQT (K/ φ), shale content Vsh (%), pore throat radius average RAll(μM), pore throat median radius RIn(μ relation m) provides and has utilized log parameter to carry out predicting reservoir in length and breadth to water sensitivityApproach.
Fig. 1 is the flow chart of a specific embodiment of reservoir water sensitivity indoor evaluation method of the present invention.
In step 101, for the major parameter that affects reservoir water-sensitive, adopt multiple linear regression analysis method to set up water sensitive indexWith core analysis chemical examination porosity, permeability, comprehensive physical parameter, shale content, the isoparametric well logging two of pore throat radiusInferior interpretation model.
Interpretation model is as follows:
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64。
In formula:
IWFor water sensitive index; φ is porosity, %; K is permeability, mD; Zwc is comprehensive physical parameter, Zwc=SQT(K/ φ); Vsh is shale content, %; RAllFor pore throat radius average, μ m; RInFor pore throat median radius, μ m.
Also verify in this step the correlation (Fig. 2) of well logging second interpretation water sensitive index and test water sensitive index. From Fig. 2Can find out, well logging second interpretation water sensitive index is good with experiment water sensitive index correlation, and the square value of coefficient correlation is0.9717, explanation can be carried out with well logging second interpretation water sensitive index the transverse and longitudinal water sensitivity prediction of the whole district.
Then utilize log data, the water sensitive index (I of calculation block diverse locationW), prediction block is in length and breadth to water sensitivity.The parameter porosity φ (%) relating in computational process; Permeability K (mD); Comprehensive physical property parameter Z wc, Zwc=SQT (K/φ); Shale content Vsh (%); Obtained all the other pore throat radius average R by log dataAll(μ m), in pore throat radiusValue RIn(μ m) can be obtained by experimental data (bringing constant into).
Table 1 is concrete analytical test data of implementing block of reservoir water sensitivity indoor evaluation method of the present invention.
408 core hole data water sensitive index second interpretation tables of data of table 1 Zheng
Iw is water sensitive index, according to the large I of value be divided into extremely strong water-sensitive, strong water-sensitive, the strong water-sensitive of middle isogonic, medium water-sensitive on the weak side,Weak water-sensitive and non-water-sensitive, divide rank in table 2.
Table 2 water-sensitive intensity is divided table
As can be seen from Figure 2, well logging second interpretation water sensitive index is good with experiment water sensitive index correlation, coefficient correlation squareValue is 0.9717, and explanation can be carried out with well logging second interpretation water sensitive index the transverse and longitudinal water sensitivity prediction of block.
Flow process enters into step 102.
In step 102, well logging second interpretation porosity.
φ＝-0.132×AC+171.98×LOG(AC)+105.986×LOG(Depth)-693.09
In formula, φ: porosity, %; AC: interval transit time after proofreading and correct, ms/m; Depth: the degree of depth, m.
Flow process enters into step 103.
In step 103, well logging second interpretation permeability.
K＝1031.55578×LOG(Depth)-0.1436×φ+11.023635×LOG(φ)-1.039×LOG(GR)-105.48857
In formula, K: permeability, mD; φ: porosity, %; Depth: the degree of depth, m; GR: natural gamma, API. StreamJourney enters into step 104.
Step 104, well log interpretation shale content.
SHI＝(GR-GRmin)/(GRmax-GRmin)
Pure shale be labeled as GRmax, clean sandstone be labeled as GRmin, SHI is commonly referred to natural gamma relative value or shale containsVolume index.
Vsh＝(2SHI×GCUR-1)/(2GCUR-1)
In formula, Vsh, well log interpretation shale content, %; ; GR: natural gamma, API; CGUR is matching rock core informationAn empirical, can determine with exponent's experience or matching rock core information. Flow process enters into step 105.
In step 105, by the parameter substitution step 101 of step 102-104 second interpretation, carry out whole district's water sensitive index in length and breadth toPrediction.
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64。
In formula: φ is well logging second interpretation porosity, %; K is well logging second interpretation permeability, mD; Zwc is comprehensive physical propertyParameter, Zwc=SQT (K/ φ); Vsh is well log interpretation shale content, %. Pore throat radius average RAll, pore throat median radiusRInCan replace with core hole mean value (constant). Flow process finishes.
Claims (9)
1. reservoir water sensitivity indoor evaluation method, is characterized in that, this reservoir water sensitivity indoor evaluation method comprises:
Step 1, utilizes core analyzing data, adopts multiple linear regression analysis method to set up the well logging secondary of water sensitive index and multiple parametersInterpretation model;
Step 2, well logging second interpretation porosity;
Step 3, well logging second interpretation permeability;
Step 4, well log interpretation shale content;
Step 5, by the logging interpretation models of the parameter substitution step 1 of second interpretation in step 2-4, carries out whole district's water-sensitive and refers toThe vertical lateral prediction of number.
2. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 1, utilizes and surveysWell data, the water sensitive index I of calculation block diverse locationW, the prediction whole district is in length and breadth to water sensitivity.
3. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 1, by water-sensitiveIndex IWAccording to large young pathbreaker's water-sensitive intensity of value be divided into extremely strong water-sensitive, strong water-sensitive, the strong water-sensitive of middle isogonic, medium water-sensitive on the weak side,Weak water-sensitive and without water-sensitive, works as IWWithin≤5 o'clock, be without water-sensitive, as 5 < IW≤ 30 o'clock is weak water-sensitive, as 30 < IWIt within≤50 o'clock, is middle isogonicWeak water-sensitive, as 50 < IWWithin≤70 o'clock, be the strong water-sensitive of middle isogonic, as 70 < IW≤ 90 o'clock is strong water-sensitive, works as IW> 90 o'clock be extremely strong water-sensitive.
4. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 1, foundationLogging interpretation models is:
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64。
In formula:
IWFor water sensitive index; φ is porosity, %; K is permeability, mD; Zwc is comprehensive physical parameter, Zwc=SQT (K/φ); Vsh is shale content, %; RAllFor pore throat radius average, μ m; RInFor pore throat median radius, μ m.
5. reservoir water sensitivity indoor evaluation method according to claim 4, is characterized in that, in step 1, and parameter holeGap degree φ, permeability K, comprehensive physical property parameter Z wc, Zwc=SQT (K/ φ), shale content Vsh are obtained by log data,Pore throat radius average RAll, pore throat median radius RInObtained by experimental data.
6. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 2, and well logging twoThe formula of inferior explanation porosity is:
φ＝-0.132×AC+171.98×LOG(AC)+105.986×LOG(Depth)-693.09
In formula, φ: porosity, %; AC: interval transit time after proofreading and correct, ms/m; Depth: the degree of depth, m.
7. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 3, and well logging twoThe formula of inferior explanation permeability is:
K＝1031.55578×LOG(Depth)-0.1436×φ+11.023635×LOG(φ)-1.039×LOG(GR)-105.48857
In formula, K: permeability, mD; φ: porosity, %; Depth: the degree of depth, m; GR: natural gamma, API.
8. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 4, is called asThe computing formula of natural gamma relative value or shaliness index SHI is:
SHI＝(GR-GRmin)/(GRmax-GRmin)
Wherein, GR: natural gamma, API, pure shale be labeled as GRmax, clean sandstone be labeled as GRmin；
The computing formula of well log interpretation shale content is:
Vsh＝(2SHI×GCUR-1)/(2GCUR-1)
In formula, Vsh, well log interpretation shale content, %; CGUR is an empirical of matching rock core information, by experience or planClosing rock core information determines.
9. reservoir water sensitivity indoor evaluation method according to claim 1, is characterized in that, in step 5, and well logging twoInferior interpretation model is:
Iw＝-7.592×φ+0.368×K+117.04×logK-109.41×Zwc+1.843×Vsh+7.38×RAll-7.187×RIn+139.64
In formula: φ is well logging second interpretation porosity, %; K is well logging second interpretation permeability, mD; Zwc is comprehensive physical propertyParameter, Zwc=SQT (K/ φ); Vsh is well log interpretation shale content, %; Pore throat radius average RAll, pore throat median radius RInReplace with core hole mean value.
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| CN107092719A (en) * | 2017-03-17 | 2017-08-25 | 中国石油天然气股份有限公司 | Water filling predominant pathway is recognized and microballoon blocks the method and device of particle diameter selection |
| CN107977505A (en) * | 2017-11-28 | 2018-05-01 | 兰州大学 | The new method that a kind of antecedent precipitation decline coefficient k determines |
| CN109387470A (en) * | 2017-08-11 | 2019-02-26 | 北京大地高科地质勘查有限公司 | A kind of matrix water-sensitive Effect Evaluation device |
| CN113552146A (en) * | 2021-09-22 | 2021-10-26 | 北京润泽创新科技有限公司 | Reservoir evaluation method and device based on digital core technology |
| CN114330023A (en) * | 2022-01-14 | 2022-04-12 | 中国石油大学(北京) | Method and device for predicting favorable reservoir distribution of tight sandstone |
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2014
- 2014-11-10 CN CN201410643515.3A patent/CN105604544A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107092719A (en) * | 2017-03-17 | 2017-08-25 | 中国石油天然气股份有限公司 | Water filling predominant pathway is recognized and microballoon blocks the method and device of particle diameter selection |
| CN107092719B (en) * | 2017-03-17 | 2020-09-04 | 中国石油天然气股份有限公司 | Method and device for identifying water injection dominant channel and selecting microsphere plugging particle size |
| CN109387470A (en) * | 2017-08-11 | 2019-02-26 | 北京大地高科地质勘查有限公司 | A kind of matrix water-sensitive Effect Evaluation device |
| CN107977505A (en) * | 2017-11-28 | 2018-05-01 | 兰州大学 | The new method that a kind of antecedent precipitation decline coefficient k determines |
| CN113552146A (en) * | 2021-09-22 | 2021-10-26 | 北京润泽创新科技有限公司 | Reservoir evaluation method and device based on digital core technology |
| CN113552146B (en) * | 2021-09-22 | 2021-12-17 | 北京润泽创新科技有限公司 | Reservoir evaluation method and device based on digital core technology |
| CN114330023A (en) * | 2022-01-14 | 2022-04-12 | 中国石油大学(北京) | Method and device for predicting favorable reservoir distribution of tight sandstone |
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Application publication date: 20160525 |