CN107292435A - A kind of Fault-block trap evaluation method based on oil columns quantitative forecast - Google Patents
A kind of Fault-block trap evaluation method based on oil columns quantitative forecast Download PDFInfo
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- 238000011156 evaluation Methods 0.000 title claims abstract description 21
- 230000000694 effects Effects 0.000 claims abstract description 12
- 230000000704 physical effect Effects 0.000 claims description 11
- 238000003325 tomography Methods 0.000 claims description 11
- 239000004215 Carbon black (E152) Substances 0.000 claims description 9
- 229930195733 hydrocarbon Natural products 0.000 claims description 9
- 150000002430 hydrocarbons Chemical class 0.000 claims description 9
- 230000035699 permeability Effects 0.000 claims description 6
- 230000015572 biosynthetic process Effects 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 239000004576 sand Substances 0.000 claims description 4
- 238000006073 displacement reaction Methods 0.000 claims description 3
- 238000002224 dissection Methods 0.000 claims description 3
- 239000003973 paint Substances 0.000 claims description 3
- 239000000463 material Substances 0.000 claims 1
- 238000010219 correlation analysis Methods 0.000 abstract description 4
- 238000005553 drilling Methods 0.000 abstract description 3
- 238000000034 method Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000007789 sealing Methods 0.000 description 3
- 239000011435 rock Substances 0.000 description 2
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- 238000002591 computed tomography Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
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- 239000003208 petroleum Substances 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
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Abstract
The invention discloses a kind of Fault-block trap evaluation method based on oil columns quantitative forecast.Comprise the following steps：1) Fault-block trap master control fault Activity Evaluation to be evaluated；2) Fault-block trap oil columns Quantitative Prediction Model is set up；Anatomical study area is into the accumulating condition for hiding Fault-block trap, using SPSS softwares, carry out partial Correlation Analysis, find out Fault-block trap oil columns Dominated Factors, the multiple regression expression formula of oil columns and these Dominated Factors is set up, it is final to set up research area's Fault-block trap oil columns Quantitative Prediction Model；3) forecast model established above is utilized, the oil columns of trap to be evaluated are calculated, Fault-block trap exploration deployment is instructed, trap drilling prospect success rate is improved.
Description
Technical field
The invention belongs to petroleum resources field, and in particular to a kind of Fault-block trap evaluation based on oil columns quantitative forecast
Method.
Background technology
Underground oil and gas is mainly gathered in different types of trap, and the groundwork of oil-gas exploration and development is exactly to oily
Trap is drilled to find and exploit the oil gas in trap.Due to geological time tectonic movement, formd in basin big
Tomography is measured, the formation of a large amount of fault block class structural traps is caused.Therefore the structural trap that block type is interrupted in basin is oil-gas exploration
The important evaluation object of exploitation.
The oil columns of Fault-block trap are to carry out the important evaluation index of exploration, are related to the economy of drilling success and oil reservoir
Property.Due to the strict control by tomography, Fault-block trap oil reservoir is not only by accumulating condition (oil sources, reservoir, cap rock, trap, fortune
Move etc.) control, also oil gas closure is controlled by tomography, therefore fault block oil reservoir governing factor is more, it is complicated into hiding, break
Block trap oil columns are evaluated very difficult.The evaluation to Fault-block trap oil columns is mainly also built upon to tomography envelope at present
Carry out on the basis of closing property quantitative and semi-quantitative, the evaluation of accumulating condition is not accounted for substantially, therefore evaluation method is not comprehensive, comments
Valency technology there is no a kind of quantitative evaluation method of Fault-block trap oil columns based on qualitative description.For example utilize experimental data
And model, row's hydrocarbon pressure differential of computed tomography and reservoir, or the direct stress of section is calculated, calculate the oil columns of fault block.This
A little methods only considered control of the fault sealing property to reservoir height, not account for into other key elements of Tibetan, it is clear that do not have
Generality, it is impossible to promoted in the whole district, it is impossible to instruct the exploration deployment of Fault-block trap.
The content of the invention
Present invention aims at comprehensively and be not unable to quantitative assessment for what is existed in terms of the evaluation of Fault-block trap oil columns
The problem of there is provided a kind of quantitative assessment technology of brand-new Fault-block trap oil columns, and based on this assessment technique, carry out disconnected
Block evaluation of trap, and then effectively instruct exploration deployment.
It is as follows using technical scheme to reach above-mentioned purpose：
A kind of Fault-block trap evaluation method based on oil columns quantitative forecast, comprises the following steps：
1) Fault-block trap master control fault Activity Evaluation to be evaluated；
Using fault growth index, the activity periods of Fault-block trap master control fault are judged；Utilize oil gas inclusion or area
Domain data, clearly studies area's Hydrocarbon Formation Reservoirs period；Compare faulting period and Hydrocarbon Formation Reservoirs period, if faulting period
It is later than oil and gas entrapment timing, then judges that this Fault-block trap into Tibetan, will not abandon the probing of Fault-block trap；If faulting period is early
In Pool-forming time, it is judged to that following steps may be continued into Fault-block trap is hidden；
2) research area is into Tibetan Fault-block trap accumulating condition dissection；
Oil-source condition is analyzed：Statistics is into Tibetan Fault-block trap and oil sources plan range, vertical distance, itself hydrocarbon source capability
Deng；
Reservior Conditions are analyzed：Statistics is into the physical property of Tibetan Fault-block trap, single sand body thickness, physical property index, and the physical property is
Porosity and permeability, the physical property index is permeability divided by porosity and evolution etc.；
Trap condition is analyzed：Statistics is into trap area, closed amplitude, buried depth for hiding Fault-block trap etc.；
Transport poly- condition analysis：Statistics is into stratigraphic dip, strata pressure for hiding Fault-block trap etc.；
Fault Seal is analyzed：Statistics is into Tibetan Fault-block trap tomography paint factor, difference of displacement pressure, section direct stress
Deng；
3) oil columns Quantitative Prediction Model is set up；
Using SPSS softwares, carry out into Tibetan Fault-block trap oil columns and various accumulating condition quantizating index in step 2
Between partial Correlation Analysis, find out the factor of Fault-block trap oil columns good relationship, be determined as the master controls of oil columns because
Element, sets up oil columns and Dominated Factors multiple regression expression formula, sets up research area's Fault-block trap oil columns quantitative forecast mould
Type；
4) model established above is utilized, carries out trap oil columns to be evaluated and calculates.
It is further comprising the steps of by such scheme：
Carry out target preferably according to the oil columns of calculating, instruct exploration deployment；By actual probing, by increasing sample
Mode further correct the oil columns Quantitative Prediction Model.
The present invention has the beneficial effect that relative to prior art：
By anatomical study area into the accumulating condition for hiding Fault-block trap, using statistical analysis software, fault block circle is searched out
The Dominated Factors of oil columns are closed, and establish the Quantitative Prediction Model of oil columns, the oil-containing of trap to be evaluated can be calculated
Highly, exploration deployment is instructed, Fault-block trap probing success rate is improved.
Brief description of the drawings
Fig. 1：Fault-block trap evaluation method flow chart based on oil columns quantitative forecast；
Fig. 2：Jiangling Depression faulting period and classification chart；
Fig. 3：Jiangling Depression Fault-block trap reservoir height governing factor partial Correlation Analysis figure.
Embodiment
Following examples further explain technical scheme, but not as limiting the scope of the invention.
Fault-block trap evaluation method of the invention based on oil columns quantitative forecast, referring to the drawings shown in 1.Specifically, will
Technical solution of the present invention is applied in In Jianghan Basin Jiangling Depression, below by taking Jiangling Depression Fault-block trap as an example, illustrates this hair
Bright applying step.
First, Fault-block trap master control fault Activity Evaluation to be evaluated
1st, by the statistics to Jiangling Depression fault growth index, find mainly there are the activity periods of five types.
2nd, found by Jiangling Depression Fluid-inclusion analysis, Jiangling Depression oil gas is mainly arranged during hydrocarbon period is Jing He towns group
Later stage.
If the 3, tomography sizing period is later than Jing He towns group latter stage, tomography does not have seal-off effect, or trap forming period
Evening, trap into Tibetan, does not abandon the probing of this trap.Conversely, tomography has certain seal-off effect.Specifically, Jiangling Depression breaks
Layer activity periods and classification chart, referring to the drawings shown in 2.The master control fault activity periods of Jiangling Depression Fault-block trap for example to be evaluated are such as
Fruit is I, II, III type, then with certain closure, it is proposed that the evaluation followed the steps below；If the activity periods of tomography are
IVth, V type, then without closure, it is proposed that abandon trap drilling prospect.
2nd, into Tibetan Fault-block trap accumulating condition dissection；
1st, oil-source condition
Jiangling Depression is counted into Tibetan trap and oil sources plan range, vertical distance, ability of the hydrocarbon source rock of itself etc..
2nd, Reservior Conditions
Count Jiangling Depression into Tibetan Fault-block trap reservoir physical property (porosity and permeability), single sand body thickness, thing
Sex index (permeability divided by porosity and evolution) etc..
3rd, trap condition
Jiangling Depression is counted into trap area, closed amplitude, buried depth of Fault-block trap of Tibetan etc..
4th, poly- condition is transported
Jiangling Depression is counted into stratigraphic dip, strata pressure of Fault-block trap of Tibetan etc..
5th, Fault-Sealing condition
Jiangling Depression is counted into paint factor, difference of displacement pressure and normal pressure of fault surface of Fault-block trap tomography of Tibetan etc..
3rd, oil columns Quantitative Prediction Model is set up
By the parameter counted in step 2, using SPSS softwares, carry out the partial Correlation Analysis with oil columns, find stratum
Inclination angle, physical property index, section direct stress, trap amplitude and trap and the vertical range correlation at Pai Ting centers are good, see Fig. 3 institutes
Show.These factors also represent the poly- condition of fortune, Reservior Conditions, Fault-Sealing condition, trap condition and oil-source condition respectively, are to contain
The Dominated Factors of oily height.
SPSS softwares are recycled, multifactor multiple linear regression will be carried out with oil columns by five main contral parameters above, obtained
To Jiangling Depression Fault-block trap reservoir height Quantitative Prediction Model：
H=2.699* θ+0.115*h+51.523*k-1.3*P-0.076*L+42.499 R2=0.964
In formula：H：Oil column thickness, m；θ：Stratum (sand body) inclination angle, °；h：Trap amplitude, m；k：Physical property index, it is immeasurable
Guiding principle；P：Section direct stress, MPa；L：Oil reservoir is apart from Ting Yuan centers vertical range, m.
4th, exploration deployment and Modifying model
Using oil columns Quantitative Prediction Model established above, applied in Jiangling Depression, husky 32 well of deployment is pre-
Survey oil columns be 125m, actual oil column thickness be 120m, absolute error is only 5m, and relative error is 4.2%, error compared with
It is small, preferably direct exploration deployment.Increase husky 32 well fault block oil reservoir sample simultaneously, Jiangling Depression Fault-block trap is have modified again
Oil columns Quantitative Prediction Model.
Claims (2)
1. a kind of Fault-block trap evaluation method based on oil columns quantitative forecast, it is characterised in that comprise the following steps：
1) trap master control fault Activity Evaluation to be evaluated；
Using fault growth index, the activity periods of Fault-block trap master control fault are judged；Provided using oil gas inclusion or region
Material, clearly studies area's Hydrocarbon Formation Reservoirs period；Compare faulting period and Hydrocarbon Formation Reservoirs period, if faulting period is later than
Oil and gas entrapment timing, then judge that this Fault-block trap into Tibetan, will not abandon the probing of Fault-block trap；If faulting period earlier than into
The Tibetan phase, it is judged to that following steps may be continued into Fault-block trap is hidden；
2) research area is into Tibetan Fault-block trap accumulating condition dissection；
Oil-source condition is analyzed：Statistics is into Tibetan Fault-block trap and oil sources plan range, vertical distance, itself hydrocarbon source capability etc.；
Reservior Conditions are analyzed：Statistics is into the physical property of Tibetan Fault-block trap, single sand body thickness, physical property index, and the physical property is oil reservoir
Porosity and permeability, the physical property index is reservoir permeability divided by porosity and evolution etc.；
Trap condition is analyzed：Statistics is into trap area, closed amplitude, buried depth for hiding Fault-block trap etc.；
Transport poly- condition analysis：Statistics is into stratigraphic dip, strata pressure for hiding Fault-block trap etc.；
Fault Seal is analyzed：Statistics is into Tibetan Fault-block trap tomography paint factor, difference of displacement pressure, section direct stress etc.；
3) oil columns Quantitative Prediction Model is set up；
Using SPSS softwares, carry out into the partial correlation hidden between Fault-block trap oil columns and various accumulating condition quantizating index
Analysis, finds out the factor of Fault-block trap oil columns good relationship, these are exactly the Dominated Factors of oil columns, set up oil-containing
Height and Dominated Factors multiple regression expression formula, that is, establish research area's Fault-block trap oil columns Quantitative Prediction Model；
4) trap oil columns to be evaluated are calculated：
Using the research area Fault-block trap oil columns Quantitative Prediction Model of foundation, trap oil columns to be evaluated are calculated.
2. the Fault-block trap evaluation method as claimed in claim 1 based on oil columns quantitative forecast, it is characterised in that also include
Following steps：
Carry out target preferably according to the oil columns of calculating, instruct exploration deployment；By actual probing, by the side for increasing sample
Formula further corrects the oil columns Quantitative Prediction Model.
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Cited By (5)
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| CN108643896A (en) * | 2018-04-16 | 2018-10-12 | 中国石油大学(华东) | A kind of oil column thickness quantitative evaluation method based on fault barrier |
| CN111812713A (en) * | 2020-04-20 | 2020-10-23 | 中国石油天然气股份有限公司 | Broken block trap determining method, exploration auxiliary method and device |
| CN112065370A (en) * | 2020-09-04 | 2020-12-11 | 中国石油大学(北京) | Method and device for evaluating oil-gas-containing property of broken block trap |
| WO2021008630A1 (en) * | 2019-07-18 | 2021-01-21 | 中国石油天然气股份有限公司 | Method, apparatus, and system for quantitative analysis of sealing strength of trap fault |
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| CN111812713A (en) * | 2020-04-20 | 2020-10-23 | 中国石油天然气股份有限公司 | Broken block trap determining method, exploration auxiliary method and device |
| CN112065370A (en) * | 2020-09-04 | 2020-12-11 | 中国石油大学(北京) | Method and device for evaluating oil-gas-containing property of broken block trap |
| CN112065370B (en) * | 2020-09-04 | 2022-05-17 | 中国石油大学(北京) | Method and device for evaluating oil-gas-containing property of broken block trap |
| 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 |
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Effective date of registration: 20200106 Address after: 100728 Beijing, Chaoyangmen, North Street, No. 22, No. Applicant after: China Petrochemical Co., Ltd. Applicant after: Exploration and Development Research Institute of SINOPEC Jianghan Oilfield Branch Company Address before: 430223, No. 18, Garden Road, East Lake hi tech Zone, Hubei, Wuhan Applicant before: Exploration and Development Research Institute of SINOPEC Jianghan Oilfield Branch Company |
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Application publication date: 20171024 |