CN104063626A - Predication method of outer-source entrapment fullness degree - Google Patents
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Abstract
The invention relates to a predication method of the outer-source entrapment fullness degree. The method comprises the steps that nine geological factors of entrapment depth, a sand body inclination angle, sand body volume, fault sealing performance, distance between entrapment and an oil source fault, cover layer thickness, cover layer quality, cover layer mobility and residual pressure which are relevant to the outer-source entrapment fullness degree are selected; entrapment with the same oil deposit type under the same structural setting is selected, the nine factors and the computed fullness degree of the entrapment are obtained respectively, scatter diagrams are drawn respectively, and the relation of a single factor and the entrapment fullness degree is obtained through a fitting function; through multiple linear regression, a predication model of the entrapment fullness degree is established for the single factor relation; and model testing and correction are carried out. The predication model is high in pertinence, under the same structural setting, identical oil deposit type entrapment predication accuracy is high, the technical problem that outer-source entrapment fullness degree predication is hard is solved, the unknown outer-source entrapment fullness degree can be predicted in a quantitative mode, and significance is achieved in guiding of oil gas exploration and deployment.
Description
Technical field
The present invention relates to a kind of method of predicting oil/gas, specifically, relate to the method for oil gas full level in unknown its source trap of a kind of comprehensive geology parameter prediction.
Background technology
The prediction of trap degree of filling is the important ring in petroleum prospecting work, before drilling well, for fear of prospect pit failure, usually wishes to go out the oil-gas possibility of trap by Accurate Prediction.
At present more about the Forecasting Methodology of HC potential of traps, include geologic risk probabilistic method, Statistics Method, fuzzy mathematics method, neural network, Grey System Method, series of strata analytic approach, geophysical method etc., these methods are summed up by the classification to geologic parameter, set up the oil-gas possibility of corresponding formula prediction trap, and less for the prediction of rich accumulation of oil and gas series of strata and Oil-gas Accumulation Types.These methods still can not the underground trap of Accurate Prediction oily situation, there is larger error.
Only once spattering brightness predicts the trap degree of filling of the lithologic deposit in hollow district, the Dominated Factors of pointing out dissimilar reservoir fullness is different: 1. for be gathered into the oil reservoir of Tibetan because of lithologic pinch out, the oozing property of hole of reservoir and the geometric properties of sand body are the most important controlling factors of degree of filling, secondly be oil-gas migration condition, and the conditioning in " source " is smaller; 2. for being subject to the Composite Reservoir of tomography and lithology co-controlling, the first controlling factor of its degree of filling is oil-gas migration condition, that is, the distance at Ju Shengting center, tomography quantity relevant to sand body and surplus pressure, be secondly the physical property of reservoir and the geometric properties of sand body.
Application publication number is CN103698494A, patent name is the method for a < < definite lithologic trap hydrocarbon saturation and the patented claim of device > >, is mainly the prediction for the lithologic deposit in hydrocarbon source rock.Because the influence factor of the type trap forming hydrocarbon-bearing pool is less, mainly that the factor of porosity by obtaining each point of study area, the degree of depth of correspondence and the hydrocarbon saturation of actual measurement are carried out scatter diagram drafting, matching changes formula and obtains, and what emphasize is the relation between interface-potential and hydrocarbon saturation.
In addition, forefathers have summed up the Forecasting Methodology that has promoted HC potential of traps in relatively complete source, concluded the geologic parameter that affects HC potential of traps in source, but not yet set up the forecast model of trap degree of filling outside source, and for rich accumulation of oil and gas district, the oil gas of the overwhelming majority is mainly distributed in outside source, be its source hydrocarbon-bearing pool, become Tibetan complicated condition changeable, influence factor differs, and prediction difficulty is larger.On the other hand, subsurface geology situation is complicated, be subject to the complex effects of the geologic agents such as structural belt, Oil-gas Accumulation Types, its source trap degree of filling is not only subject to the impact of single factors, but the result of a plurality of factor co-controllings, from source storage static condition, to dynamic conditions such as migration, preservations, all likely become the factor that affects trap degree of filling, and sign identical conditions may there be a plurality of parameters, the very difficult degree of filling of predicting accurately different traps of general normalization formula.
Not yet suitable method is carried out the prediction of its source trap degree of filling at present.
Summary of the invention
According to above-mentioned deficiency, point out, the object of the present invention is to provide a kind of thinking and method of degree of filling forecast model of its source trap, the outer trap oily situation of prediction source, reduces exploration risk effectively.
For achieving the above object, technical program of the present invention lies in: a kind of Forecasting Methodology of its source trap degree of filling, it comprises following steps:
(1) choose influence factor: choose nine geologic agents relevant to its source trap degree of filling, be respectively trap buried depth F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, trap to Source fault apart from F5, depth of cover F6, cap rock quality F7, fault activity F8 and surplus pressure F9;
(2) analysis list factor analysis: choose hydrocarbon-bearing pool outside the source of same type under same structural setting, depth of burial F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, the trap of obtaining respectively place trap to Source fault apart from F5, depth of cover F6, cap rock quality F7, fault activity F8 and surplus pressure F9, and calculate the degree of filling of trap reality, draw respectively the scatter diagram of each factor and degree of filling, by fitting function, obtain the funtcional relationship of the factor of placing an order and degree of filling: F
i=D (X
i), i=1,2 ..., 9;
(3) set up forecast model: above-mentioned single factor relation is set up to the multi-factor Estimation Model of its source trap degree of filling by multiple linear regression:
Wherein, a
ifor weight coefficient;
(4) model testing and correction.
Preferably: described fault sealing property obtains by tomography mud stone ratio SGR method.
Preferably: described cap rock quality obtains by sonic time difference.
Preferably: described fault activity obtains by growth index analysis.
Preferably: described known Forming Petroleum Traps degree of filling calculates acquisition by volumetric method.
Preferably: the actual measurement degree of filling of described Forming Petroleum Traps calculates acquisition by volumetric method.
Accompanying drawing explanation
Fig. 1 is the graph of a relation of its source trap degree of filling and the trap degree of depth in specific embodiment.
Fig. 2 is the graph of a relation at its source trap degree of filling and sand body inclination angle in specific embodiment.
Fig. 3 is the graph of a relation of its source trap degree of filling and sand body volume in specific embodiment.
Fig. 4 is the graph of a relation of its source trap degree of filling and fault sealing property in specific embodiment.
Fig. 5 be in specific embodiment its source trap degree of filling and trap apart from the graph of a relation of Source fault distance.
Fig. 6 is the graph of a relation of its source trap degree of filling and depth of cover in specific embodiment.
Fig. 7 is the graph of a relation of its source trap degree of filling and cap rock quality in specific embodiment.
Fig. 8 is the graph of a relation of its source trap degree of filling and fault activity in specific embodiment.
Fig. 9 is the graph of a relation between its calculated value of forecast model of the present invention and actual value.
Figure 10 is Technology Roadmap of the present invention.
Embodiment
Below in conjunction with specific embodiment, the present invention will be further described.
Take area, Bohai gulf basin field of razor clam island is example, illustrates modeling process.The main oil-bearing series in area, Bohai gulf basin field of razor clam island is Neogene System, and lithology-tomography oil reservoir of main body zone of fracture Ng group is typical its source oil reservoir, and tomography Dui Gai district Hydrocarbon Formation Reservoirs has vital role.Study area oil reservoir buries more shallow, is normal pressure system, and concrete operation step is as follows:
1, choose influence factor: choose trap degree of depth F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, trap apart from Source fault apart from F5, depth of cover F6, cap rock quality F7, eight geologic agents of fault activity F8 the geologic parameter as forecast model.
This is that tomography plays important translocation because its source hydrocarbon-bearing pool is conventionally far away apart from Sheng Ting center, grows the multiple Trap Typesofs such as fault trap, lithologic trap and combination trap.For single oil reservoir, its degree of filling is subject to the control of sand body morphology and sealing condition.Because this district is normal pressure system, surplus pressure is zero, and F9 factor is meaningless, and therefore choosing above-mentioned eight factors carries out analysis modeling.
2, analysis list factor analysis: degree of depth F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, the trap of obtaining respectively the place trap of known oil reservoir to Source fault apart from F5, depth of cover F6, cap rock quality F7, fault activity F8 the degree of filling with corresponding calculating, draw respectively scatter diagram, by fitting function, obtain the relation formula of following concrete single factor and trap degree of filling:
The relation of degree of filling and the trap degree of depth: F
1=41.03e
-0.0032xr
2=0.318
The relation at degree of filling and sand body inclination angle: F
2=0.7759e
-0.4616xr
2=0.1474
The relation of degree of filling and sand body volume: F
3=0.0001x
2-0.0154x+0.7576 R
2=0.2734
The relation of degree of filling and fault sealing property: F
4=2.4524x
-1.0547r
2=0.866
Degree of filling and trap are to the relation of Source fault distance: F5=0.26Ln (x)-1.2349 R
2=0.3458
The relation of degree of filling and depth of cover: F
6=0.2378Ln (x)-0.0706 R
2=0.2182
The relation of degree of filling and cap rock quality: F
7=3036e
-0.0237xr
2=0.3497
The relation of degree of filling and fault activity: F
8=2E-07e
13.769xr
2=0.3688
Wherein, fault sealing property obtains by tomography mud stone ratio SGR method.Cap rock quality obtains by sonic time difference.Fault activity obtains by growth index analysis.Degree of filling calculates acquisition by volumetric method.
According to the size of related coefficient, analyze the degree in close relations between degree of filling and each factor, the value of related coefficient is larger, and relation is closer, affects larger; Vice versa, gets rid of the very low factor of related coefficient.
The degree of filling of lithology-fault trap and sand body inclination angle, sand body volume, the trap degree of depth, cap rock quality, the trap that from above-mentioned single factor relation, can find out the main body zone of fracture in area, Bohai gulf basin field of razor clam island are negative correlation, its source trap degree of filling and fault sealing property, fault activity and being proportionate property of depth of cover apart from Source fault distance.
By coefficient R
2size can find out that each geologic agent on the strong and weak order of degree of filling impact is: fault sealing property > fault activity > cap rock quality > oil reservoir to Source fault apart from > trap degree of depth > sand body volume > depth of cover > sand body inclination angle.
3, set up forecast model: above-mentioned single factor relation is set up to the multi-factor Estimation Model of its source trap degree of filling: F=0.434 * F1+0.245 * F2+0.273 * F3+0.891 * F4+0.101 * F5-0.425 * F6-0.047 * F7-0.078 * F8-0.107R by multiple linear regression
2=0.9587;
From coefficient R
2=0.9587 can find out, the formula of matching has higher correlativity, and the error of actual value and calculated value is relatively little.Error all, within allowed band, proves that model foundation rationally, reliably.
4, model testing and correction: choose the data point of not including in model process of establishing, the forecast model formula in substitution step (3), the correctness of testing model and accuracy.Choose 4 oil reservoirs of not participating in the main body zone of fracture of model foundation and predict, predict the outcome as shown in table 1 with measured result.
Its its degree of filling of source trap that 4, table 1 is not participated in modeling predicts the outcome and measured result comparison
Predict the outcome as can be seen from Table 1 and meet well with measured result, the feasibility of formula is described.
At this, illustrate, if nine factors in above-mentioned summary of the invention are not to need to take into account completely, can screen key factor according to the actual geological condition in area to be measured.Also can judge according to the size of the related coefficient of single factor and trap degree of filling relation formula, if its facies relationship numerical value is minimum, can directly gets rid of this factor, and not consider when setting up whole forecast model.
Claims (5)
1. the Forecasting Methodology of its source trap degree of filling, is characterized in that: it comprises following steps:
(1) choose influence factor: choose nine geologic agents relevant to its source trap degree of filling, be respectively trap buried depth F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, trap apart from Source fault apart from F5, depth of cover F6, cap rock quality F7, fault activity F8 and surplus pressure F9;
(2) analysis list factor analysis: choose under same structural setting, outside the source of same type hydrocarbon-bearing pool some, obtain respectively depth of burial F1, sand body inclination angle F2, sand body volume F3, fault sealing property F4, the trap of corresponding trap and apart from F5, depth of cover F6, cap rock quality F7, fault activity F8 and surplus pressure F9, calculate the degree of filling of trap to Source fault.Draw respectively the scatter diagram of nine factors and trap degree of filling, by fitting function, obtain the relation formula of single factor and trap degree of filling: F
i=D (X
i), i=1,2 ..., 9;
(3) set up forecast model: above-mentioned single factor relation is set up to the multi-factor Estimation Model of its source trap degree of filling by multiple linear regression:
Wherein, a
ifor weight coefficient;
(4) model testing and correction: choose the data point of not including in model process of establishing, the forecast model formula in substitution step (3), the correctness of testing model and accuracy.
2. the Forecasting Methodology of its source trap degree of filling according to claim 1, is characterized in that: described fault sealing property obtains by tomography mud stone ratio SGR method.
3. the Forecasting Methodology of its source trap degree of filling according to claim 1, is characterized in that: described cap rock quality obtains by sonic time difference.
4. the Forecasting Methodology of its source trap degree of filling according to claim 1, is characterized in that: described fault activity obtains by growth index analysis.
5. the Forecasting Methodology of its source trap degree of filling according to claim 1, is characterized in that: the actual measurement degree of filling of described Forming Petroleum Traps calculates acquisition by volumetric method.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104484749A (en) * | 2014-12-04 | 2015-04-01 | 广东电网有限责任公司电力科学研究院 | Method and system used for predicting carbon emission of coal-fired power plant |
| CN105912884A (en) * | 2016-06-13 | 2016-08-31 | 江苏大学 | Crop-stem-diameter growth velocity predicting method based on physiological effect |
| CN106294890A (en) * | 2015-05-12 | 2017-01-04 | 中国石油化工股份有限公司 | A kind of sandy conglomerate bodies fracturing fracture control design case method |
| CN108052728A (en) * | 2017-12-08 | 2018-05-18 | 中国石油化工股份有限公司 | The characterizing method of lithological pool subtle passage system |
| CN108073744A (en) * | 2016-11-16 | 2018-05-25 | 中国石油化工股份有限公司 | Turbidite fan advance distance Forecasting Methodology based on geostatistics |
| CN108241904A (en) * | 2016-12-27 | 2018-07-03 | 中国石油化工股份有限公司 | Stratigraphic onlap trap oil-gas filling degree quantitative forecasting technique based on linear regression |
| CN112965108A (en) * | 2021-02-05 | 2021-06-15 | 中国石油天然气股份有限公司 | Method and system for determining vertical sealing performance of trap cover layer |
| CN113093302A (en) * | 2020-03-04 | 2021-07-09 | 中国海洋石油集团有限公司 | Three-dimensional filling migration analysis method for complex fracture zone multi-layer system oil gas |
| CN114427432A (en) * | 2020-09-11 | 2022-05-03 | 中国石油化工股份有限公司 | Method for determining development potential of residual gas in gas reservoir |
-
2014
- 2014-07-11 CN CN201410331233.XA patent/CN104063626A/en active Pending
Non-Patent Citations (6)
| Title |
|---|
| 庄梅: "埕岛地区新近系油藏充满度研究", 《万方学位论文》 * |
| 张凤奇等: "辽河西部凹陷复杂构造圈闭含油性主控因素及定量模式", 《吉林大学学报（地球科学版）》 * |
| 张凤奇等: "辽河西部凹陷岩性圈闭油充满度及其主控因素分析", 《万方学术会议数据库》 * |
| 曾溅辉等: "东营凹陷岩性圈闭油气充满度及其主控因素", 《石油与天然气地质》 * |
| 蒋有录等: "渤海湾盆地饶阳凹陷新近系油气富集特点与主控因素", 《石油学报》 * |
| 黄淑芳: "大民屯凹陷潜山油气藏油气富集主控因素分析", 《特种油气藏》 * |
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| CN106294890A (en) * | 2015-05-12 | 2017-01-04 | 中国石油化工股份有限公司 | A kind of sandy conglomerate bodies fracturing fracture control design case method |
| CN105912884A (en) * | 2016-06-13 | 2016-08-31 | 江苏大学 | Crop-stem-diameter growth velocity predicting method based on physiological effect |
| CN105912884B (en) * | 2016-06-13 | 2018-06-26 | 江苏大学 | A kind of stem of plant growth in thickness rate prediction method based on physiological effect |
| CN108073744B (en) * | 2016-11-16 | 2021-08-20 | 中国石油化工股份有限公司 | Turbidimetric fan propulsion distance prediction method based on geology statistics |
| CN108073744A (en) * | 2016-11-16 | 2018-05-25 | 中国石油化工股份有限公司 | Turbidite fan advance distance Forecasting Methodology based on geostatistics |
| CN108241904A (en) * | 2016-12-27 | 2018-07-03 | 中国石油化工股份有限公司 | Stratigraphic onlap trap oil-gas filling degree quantitative forecasting technique based on linear regression |
| CN108052728A (en) * | 2017-12-08 | 2018-05-18 | 中国石油化工股份有限公司 | The characterizing method of lithological pool subtle passage system |
| CN113093302A (en) * | 2020-03-04 | 2021-07-09 | 中国海洋石油集团有限公司 | Three-dimensional filling migration analysis method for complex fracture zone multi-layer system oil gas |
| CN113093302B (en) * | 2020-03-04 | 2022-04-15 | 中国海洋石油集团有限公司 | Three-dimensional filling migration analysis method for complex fracture zone multi-layer system oil gas |
| CN114427432A (en) * | 2020-09-11 | 2022-05-03 | 中国石油化工股份有限公司 | Method for determining development potential of residual gas in gas reservoir |
| CN114427432B (en) * | 2020-09-11 | 2024-04-26 | 中国石油化工股份有限公司 | Method for determining development potential of residual gas in gas reservoir |
| CN112965108A (en) * | 2021-02-05 | 2021-06-15 | 中国石油天然气股份有限公司 | Method and system for determining vertical sealing performance of trap cover layer |
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