CN111610560A - Oil gas prediction method based on seismic longitudinal frequency spectrum time shift - Google Patents
Oil gas prediction method based on seismic longitudinal frequency spectrum time shift Download PDFInfo
- Publication number
- CN111610560A CN111610560A CN201910144623.9A CN201910144623A CN111610560A CN 111610560 A CN111610560 A CN 111610560A CN 201910144623 A CN201910144623 A CN 201910144623A CN 111610560 A CN111610560 A CN 111610560A
- Authority
- CN
- China
- Prior art keywords
- seismic
- time shift
- frequency spectrum
- target layer
- longitudinal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/624—Reservoir parameters
Abstract
The invention provides an oil-gas prediction method based on seismic longitudinal frequency spectrum time shift, which comprises the following steps of: determining the position of a target layer, and analyzing the stratum heterogeneity of the target layer; according to the stratum heterogeneity of the target layer, respectively taking a time window above and below the target layer; calculating the seismic original frequency response before the same seismic wave penetrates into the target layer and the background field frequency response after the same seismic wave penetrates through the target layer in time windows above and below the target layer respectively; after the seismic original frequency response and the background field frequency response are subjected to normalization processing, calculating the frequency spectrum difference of the seismic original normalized frequency spectrum and the background field normalized frequency spectrum, and obtaining longitudinal frequency spectrum time shift when the seismic waves pass through a target layer; and analyzing the probability of the oil gas in the target layer by utilizing the characteristics of the longitudinal frequency spectrum time shift. The method utilizes the longitudinal frequency spectrum time shifting characteristics caused by the oil-gas reservoir to predict oil and gas, and solves the problem of the multi-solution property of oil-gas prediction caused by the transverse heterogeneity of the stratum in the prior art.
Description
Technical Field
The invention belongs to the technical field of petroleum and natural gas seismic exploration and development, and particularly relates to an oil-gas prediction method based on seismic longitudinal frequency spectrum time shifting.
Background
How to accurately identify hydrocarbon-bearing reservoirs has been a great concern in oil and gas exploration and development. How to utilize seismic data and adopt a feasible method to realize oil-gas identification has important significance for expanding oil-gas reserves and improving the exploration value of discovered oil-gas reservoirs.
The primary cause of seismic wave attenuation is formation absorption, which is one of the important characteristics of the subsurface medium. When seismic waves propagate in reservoirs where oil and gas are gathered, the presence of oil and gas does not affect the seismic signals of all frequency components. Usually it only changes part of the frequency energy, which will cause attenuation of high frequency energy and relative enhancement of low frequency energy when the reservoir contains oil gas. A "low frequency ghost" phenomenon of strong low frequency amplitude is generated below the reservoir. In the low-frequency section, the characteristic of the low-frequency ghost is obvious, namely the seismic wave reflection energy of the low-frequency ghost is stronger than that of the reservoir; in the high frequency band, the seismic wave reflection energy of the "low frequency ghost" is weaker than that of the reservoir and decreases with increasing frequency.
Therefore, in recent years, the time-frequency analysis technology is widely applied to prediction of the oil-gas enrichment area. The prior art is mainly divided into the following two categories.
The first type is that main high frequency band and low frequency band of energy attenuation change of a reservoir layer caused by oil and gas are determined through spectrum analysis, seismic data frequency division is carried out by utilizing frequency division means such as wavelet transformation, target frequency band information is extracted to carry out transverse and longitudinal comparison, and therefore the oil and gas range is determined. The Yingxing (2014) carries out low-frequency accompanying image rapid identification and application through Marr wavelet transformation and a three-primary color display technology; chenpeng (2013) predicts the oil and gas content of a reservoir through a spectral decomposition technology, seismic slices with different frequencies can be used for effective analysis of a target zone through the spectral decomposition technology, and an author selects a 25Hz tuning body to verify the oil and gas absorption coefficient of a wedge-shaped body.
The second category is methods that make predictions by using the rapid decay in energy of seismic signals as they pass through hydrocarbon-bearing reservoirs. When the geological body contains fluid (such as oil and gas), the attenuation of seismic wave energy is caused, and the attenuation of high-frequency energy of the seismic wave is larger than that of low-frequency energy. The Teng-team residue (2012) extracts the frequency attenuation gradient attribute by utilizing the characteristic of the fast and slow attenuation of the seismic wave energy to realize the underground oil-gas prediction. Dungjian nu (2016) was studied and implemented for hydrocarbon prediction technology using high frequency energy attenuation.
Due to the difference of the transverse heterogeneity of the stratum, the oil and gas prediction method based on the frequency spectrum attenuation often generates obvious multi-solution. For clastic rock, the transverse lithology and physical property differences caused by different sedimentary facies zones can also generate differential absorption attenuation on the propagation of seismic waves; for carbonate rocks, the absorption attenuation of seismic waves and the energy attenuation caused by oil-containing gas cannot be clearly distinguished due to different development degrees of transverse fractures and differential erosion of holes. In fact, the two types of hydrocarbon prediction technologies based on spectrum analysis do not take into account the seismic wave attenuation difference caused by formation and structure difference, but the reliability of the hydrocarbon prediction result based on the method greatly depends on the heterogeneity degree of the underground formation. Therefore, how to solve the problem of multiple solutions caused by the lateral heterogeneity of the stratum is a technical problem to be solved to obtain a hydrocarbon prediction result with higher accuracy.
Disclosure of Invention
Aiming at the technical problems, the invention provides a novel oil-gas prediction method based on seismic longitudinal frequency spectrum time shift. The method utilizes the dual characteristics of high-frequency attenuation and low-frequency enhancement of seismic waves of the oil-gas reservoir, and carries out stratum oil-gas prediction by analyzing the relative change of a seismic frequency spectrum along a longitudinal time section.
The method comprises the following steps:
s100, determining the position of a target layer, and analyzing the stratum heterogeneity of the target layer;
s200, respectively taking a time window above and below a target layer according to the stratum heterogeneity of the target layer;
step S300, calculating the seismic original frequency response before the same seismic wave penetrates into the target layer and the background field frequency response after the same seismic wave penetrates through the target layer in the time windows above and below the target layer respectively;
step S400, respectively carrying out normalization processing on the seismic original frequency response and the background field frequency response to obtain a seismic original normalized frequency spectrum and a background field normalized frequency spectrum;
step S500, calculating the frequency spectrum difference between the seismic original normalized frequency spectrum and the background field normalized frequency spectrum to obtain longitudinal frequency spectrum time shift when the seismic waves pass through a target layer;
and S600, analyzing the probability of the oil gas in the target layer by utilizing the characteristics of longitudinal frequency spectrum time shift.
According to an embodiment of the present invention, in the step S100, the position of the target zone is determined according to the well-seismic calibration result.
According to an embodiment of the present invention, in the step S100, a stratigraphic heterogeneity analysis is performed on the target zone based on the well drilling and the stratigraphic geological data.
According to an embodiment of the present invention, in the step S200, a time window is taken above the destination layer and below the destination layer, and the two time window windows are equal in length.
Alternatively, in step S200, a time window is taken above the destination layer and below the destination layer, and the two time windows have different lengths.
According to an embodiment of the present invention, the step S600 includes: and if the longitudinal frequency spectrum time shift is characterized in that the time shift of the low frequency band is a negative value and the time shift of the high frequency band is a positive value, judging that the target layer contains oil gas.
According to an embodiment of the present invention, the step S600 further includes: if the absolute value of the time shift negative value of the low frequency band and the absolute value of the time shift positive value of the high frequency band of the longitudinal frequency spectrum time shift are larger, the probability of the oil gas in the target layer is higher. .
According to an embodiment of the invention, in step S600, the longitudinal spectral time shift is characterized by a minimum and a maximum of the longitudinal spectral time shift.
According to an embodiment of the present invention, the step S600 includes: and calculating the difference between the maximum value and the minimum value of the longitudinal frequency spectrum time shift, and analyzing the probability of oil and gas in the target layer according to the difference.
Wherein, the probability of the oil gas in the target layer is analyzed according to the difference value, which comprises the following steps: the greater the difference, the higher the probability of the target formation containing oil gas.
Compared with the prior art, the invention has the following advantages or beneficial effects:
the invention provides a novel oil-gas prediction method based on seismic longitudinal frequency spectrum time shifting. The method judges the hydrocarbon-containing probability by comparing and analyzing the spectral characteristics of the hydrocarbon-containing reservoir section and the background field, solves the problem of hydrocarbon-containing prediction ambiguity caused by the transverse heterogeneity of the stratum in the prior art, and has stronger adaptability to complex strata.
The conventional spectrum analysis only utilizes the spectrum abnormity caused by the absorption attenuation of oil and gas to seismic waves to carry out transverse difference comparison, and when stratum has strong transverse heterogeneity (such as lithology, physical property change or fracture caused by structure), the method has obvious ambiguity for oil and gas prediction. The invention utilizes the frequency spectrum time shift change caused by the seismic wave after passing through the oil-gas reservoir and judges the oil-gas containing probability by comparing and analyzing the longitudinal difference of the same seismic channel data in the upper time window and the lower time window of the oil-gas reservoir. The obtained longitudinal frequency spectrum time shift value completely depends on the characteristics of stratum oil and gas, and factors of lithology, physical properties or structural transverse change can be eliminated to the maximum extent through time window adjustment when the frequency spectrum longitudinal time shift difference value is obtained.
Meanwhile, the existing spectral analysis oil gas prediction method mainly utilizes the characteristic of high-frequency attenuation, and the method can simultaneously utilize the characteristics of high-frequency attenuation and low-frequency enhancement of oil gas, so that the obtained prediction result has higher accuracy.
Drawings
The scope of the present disclosure may be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart illustrating the steps of a hydrocarbon prediction method according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram showing spectral attenuation caused by a hydrocarbon-bearing formation according to a first embodiment of the present invention;
FIG. 3 shows the spectral characteristics of M1 well seismic waves before and after the waves pass through the target zone in the second embodiment of the present invention;
FIG. 4 shows the spectral characteristics of M2 well seismic waves before and after the waves pass through the target zone in the second embodiment of the present invention;
fig. 5 is a plan view showing the time shift of the longitudinal spectrum of the destination layer of the M oilfield according to the second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, embodiments of the present invention are described in detail below with reference to the accompanying drawings and examples, so that how to apply technical means to solve technical problems and achieve a technical effect can be fully understood and implemented.
Example one
FIG. 1 is a flow chart of a method for hydrocarbon prediction based on seismic longitudinal spectral time shift according to an embodiment of the present invention.
As shown in fig. 1, the method fully utilizes the dual characteristics of high-frequency attenuation and low-frequency enhancement of seismic waves of a hydrocarbon-bearing reservoir, and performs hydrocarbon prediction of a target zone through the relative change of a seismic frequency spectrum along a longitudinal time section, and the specific contents are as follows:
for seismic data (seismic waves), the seismic original frequency response (f) is the hydrocarbon-bearing formation frequency response (f1) + the background field frequency response after absorption (f 2).
First, in this embodiment, the location T of the target zone is determined according to the well-seismic calibration result0And based on well drilling and formation geological dataAnd carrying out heterogeneity analysis of the target layer.
Then, on top of the destination layer (T) according to its heterogeneity0-t1) And below the destination layer (T)0+t2) Respectively taking a time window, respectively calculating the frequency spectrum f (T) of the time window0-t1) And f (T)0+t2). Wherein, f (T)0-t1) For seismic original frequency response (f), f (T) before seismic waves penetrate into the target layer0+t2) Is the background field frequency response after the seismic waves have traversed the destination layer (f 2).
Then, for two frequency spectrums f (T)0-t1) And f (T)0+t2) Respectively carrying out normalization processing to obtain the original normalized frequency spectrum F (T) of the earthquake0-t1) Normalized spectrum F (T) with background field0+t2)。
Then, the seismic original normalized spectrum F (T) is calculated0-t1) Normalizing the spectrum F (T) with the background field0+t2) The spectral difference between them. Briefly, the normalized frequency spectrum F (T) of the temporal window on the target layer is used0-t1) The normalized frequency spectrum F (T) of the lower time window is subtracted0+t2) The result is defined as the longitudinal spectral time shift Δ t. This longitudinal spectral time shift reflects the variation of the seismic spectral signature with the longitudinal time axis as the seismic waves traverse the target formation, i.e., the hydrocarbon-bearing formation frequency response (f 1).
As the attenuation conditions of frequency components of seismic waves are different when the seismic waves pass through stratums with different physical characteristics or oil-gas-containing and non-oil-gas reservoirs, the frequency spectrum characteristics and the transverse change characteristics of frequency spectrum time shift can be important bases for judging whether the reservoirs contain oil and gas.
When the target layer contains oil and gas, due to the characteristics of high-frequency attenuation and low-frequency enhancement, the longitudinal frequency spectrum time shift delta t (frequency spectrum difference) has the characteristic that the time shift of the low frequency band is a negative value and the time shift of the high frequency band is a positive value. As shown in fig. 2, the larger the absolute value of the negative time shift value of the low frequency band and the absolute value of the positive time shift value of the high frequency band of the longitudinal spectrum time shift Δ t are, the greater the probability of the formation containing oil gas is.
In view of the above, in the present invention, a parameter λ is preferably introduced to characterize the low-frequency negative low value and the high-frequency positive high value of the longitudinal spectrum time shift Δ t when the target zone contains hydrocarbons.
In one embodiment, the minimum value Δ t (min) and the maximum value Δ t (max) of the time shift Δ t of the frequency spectrum may be calculated, where λ ═ Δ t (max) - Δ t (min), and the larger the λ value is, the larger the energy of the low-frequency enhancement and the high-frequency absorption caused by the oil and gas formation is, the higher the probability of containing oil and gas is.
Of course, λ ═ Δ t (max) + at (min), or another calculation method may be used as long as the feature that the longitudinal spectrum time shift Δ t has a low-frequency negative low value and a high-frequency positive high value when the target zone contains hydrocarbons can be demonstrated.
Example two
The technical scheme of the invention is explained by the oil-gas content prediction process and the prediction result of the fracture-cavity reservoir of the M oil fields in a certain basin.
The buried depth of the M oil field carbonate reservoir, the reservoir development characteristics and the scale are controlled by the fracture characteristics, the M oil field carbonate reservoir has strong transverse heterogeneity, and an accurate fluid prediction result cannot be obtained by a conventional frequency spectrum attenuation method. M1 well was the producing well, M2 well was the drywell, and the bottom of the two wells was deep (T)0) Are the same set of destination layers. With the target layer as the target, one time window t is taken up and down1And t2Respectively acquiring seismic original frequency spectrum f (T) before seismic waves of the M1 well and the M2 well penetrate into a target layer0-t1) And the background field spectrum f (T) of the seismic waves after they have traversed the destination layer0+t2) Please refer to fig. 3 and 4. As can be seen from fig. 3, at the position of the M1 well, the seismic spectrum exhibits significant high-frequency energy absorption and low-frequency energy enhancement characteristics above and below the target zone. As can be seen from fig. 4, at the position of the M2 well, the spectral characteristics of the seismic waves after passing through the target layer are only attenuated by the primary frequency energy, which is caused by the overall absorption of the seismic waves by the formation. Thus, the longitudinal spectral time-shifting technique of the present invention can be applied to make hydrocarbon-bearing predictions in the region.
Calculating frequency spectrum f (T) of seismic data of M oil fields in whole area0-t1) And f (T)0+t2) And acquiring corresponding longitudinal spectrum time shift delta t after normalization processing. As shown in fig. 5, λ ═ Δ t (max) - Δ t (min) is calculated, and the transverse change of λ is displayed in a planar graph, so that the oil-gas prediction analysis is performed.
Through comparison and analysis with known drilling results, the change of lambda can be confirmed to be completely consistent with the oil and gas development characteristics of the region. The method for predicting the oil and gas based on the seismic longitudinal frequency spectrum time shift has high accuracy.
The above embodiments are only specific embodiments of the present invention. It is obvious that the invention is not limited to the above embodiments, but that many variations are possible. All modifications attainable by one versed in the art from the present disclosure within the scope and spirit of the present invention are to be considered as within the scope and spirit of the present invention.
Claims (10)
1. A hydrocarbon prediction method based on seismic longitudinal frequency spectrum time shift comprises the following steps:
s100, determining the position of a target layer, and analyzing the stratum heterogeneity of the target layer;
s200, respectively taking a time window above and below a target layer according to the stratum heterogeneity of the target layer;
step S300, calculating the seismic original frequency response before the same seismic wave penetrates into the target layer and the background field frequency response after the same seismic wave penetrates through the target layer in the time windows above and below the target layer respectively;
step S400, respectively carrying out normalization processing on the seismic original frequency response and the background field frequency response to obtain a seismic original normalized frequency spectrum and a background field normalized frequency spectrum;
step S500, calculating the frequency spectrum difference between the seismic original normalized frequency spectrum and the background field normalized frequency spectrum to obtain longitudinal frequency spectrum time shift when the seismic waves pass through a target layer;
and S600, analyzing the probability of the oil gas in the target layer by utilizing the characteristics of longitudinal frequency spectrum time shift.
2. The method for hydrocarbon prediction based on seismic longitudinal spectral time shift of claim 1 wherein in step S100, the location of the target zone is determined based on the well seismic calibration results.
3. The method for hydrocarbon prediction based on seismic longitudinal spectral time shift of claim 1 wherein in step S100, formation heterogeneity analysis is performed on the target formation based on well drilling and formation geology.
4. The method for hydrocarbon prediction based on seismic longitudinal spectral time shift according to claim 1, wherein in step S200, a time window is taken above the target zone and below the target zone, and the two time windows are equal in length.
5. The method for hydrocarbon prediction based on seismic longitudinal spectral time shift according to claim 1, wherein in step S200, a time window is taken above the target zone and below the target zone, and the two time windows have different lengths.
6. The method for hydrocarbon prediction based on seismic longitudinal spectral time shifts of claim 1, wherein said step S600 comprises: and if the longitudinal frequency spectrum time shift is characterized in that the time shift of the low frequency band is a negative value and the time shift of the high frequency band is a positive value, judging that the target layer contains oil gas.
7. The method for hydrocarbon prediction based on seismic longitudinal spectral time shifts of claim 6, wherein said step S600 further comprises: if the absolute value of the time shift negative value of the low frequency band and the absolute value of the time shift positive value of the high frequency band of the longitudinal frequency spectrum time shift are larger, the probability of the oil gas in the target layer is higher.
8. The method for seismic longitudinal spectral time shift based hydrocarbon prediction of claim 1 wherein in step S600, the longitudinal spectral time shift is characterized by a minimum and a maximum of the longitudinal spectral time shift.
9. The method for hydrocarbon prediction based on seismic longitudinal spectral time shift of claim 8, wherein said step S600 comprises: and calculating the difference between the maximum value and the minimum value of the longitudinal frequency spectrum time shift, and analyzing the probability of oil and gas in the target layer according to the difference.
10. The method of claim 9, wherein analyzing the probability of hydrocarbon in the target zone based on the magnitude of the difference comprises: the greater the difference, the higher the probability of the target formation containing oil gas.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910144623.9A CN111610560A (en) | 2019-02-26 | 2019-02-26 | Oil gas prediction method based on seismic longitudinal frequency spectrum time shift |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910144623.9A CN111610560A (en) | 2019-02-26 | 2019-02-26 | Oil gas prediction method based on seismic longitudinal frequency spectrum time shift |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111610560A true CN111610560A (en) | 2020-09-01 |
Family
ID=72200079
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910144623.9A Pending CN111610560A (en) | 2019-02-26 | 2019-02-26 | Oil gas prediction method based on seismic longitudinal frequency spectrum time shift |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111610560A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305943A (en) * | 2011-07-22 | 2012-01-04 | 中国石油天然气股份有限公司 | Seismic wavelet attenuation spectrum-based oil and gas detecting method and device |
| CN103197347A (en) * | 2013-02-20 | 2013-07-10 | 中国海洋石油总公司 | Oil gas absorption and analysis predicting method based on self-adaptation time window |
| CN105403915A (en) * | 2014-09-04 | 2016-03-16 | 中国石油化工股份有限公司 | Method for extracting instantaneous absorption attenuation parameters of stratum based on spectrum simulation |
| US10191168B2 (en) * | 2016-01-12 | 2019-01-29 | Cgg Services Sas | AVA compliant pre-stack frequency spectrum enhancement of seismic data |
-
2019
- 2019-02-26 CN CN201910144623.9A patent/CN111610560A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305943A (en) * | 2011-07-22 | 2012-01-04 | 中国石油天然气股份有限公司 | Seismic wavelet attenuation spectrum-based oil and gas detecting method and device |
| CN103197347A (en) * | 2013-02-20 | 2013-07-10 | 中国海洋石油总公司 | Oil gas absorption and analysis predicting method based on self-adaptation time window |
| CN105403915A (en) * | 2014-09-04 | 2016-03-16 | 中国石油化工股份有限公司 | Method for extracting instantaneous absorption attenuation parameters of stratum based on spectrum simulation |
| US10191168B2 (en) * | 2016-01-12 | 2019-01-29 | Cgg Services Sas | AVA compliant pre-stack frequency spectrum enhancement of seismic data |
Non-Patent Citations (5)
| Title |
|---|
| 中国地球物理学会: "《中国地球物理 2012》", 31 October 2012, 合肥：中国科学技术大学出版社 * |
| 张世民等: "《东濮凹陷文东地区层序地层格架与油气成藏条件分析》", 30 September 2004, 武汉：中国地质大学出版社 * |
| 方志雄: "《延川南煤层气田勘探开发关键技术及应用》", 30 June 2017, 北京：地质出版社 * |
| 李西栋等: "《最新智能化采矿新工艺新技术与计算机管理技术应用手册 第1卷》", 31 August 2006, 中国矿业出版社 * |
| 赵一民等: "地震频谱衰减属性在松辽盆地南部深层火山岩气藏预测中的应用", 《油气地质与采收率》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111158044B (en) | Buried hill fracture reservoir body oil reservoir prediction method | |
| Huang et al. | Use of nonlinear chaos inversion in predicting deep thin lithologic hydrocarbon reservoirs: A case study from the Tazhong oil field of the Tarim Basin, China | |
| Naseer et al. | Porosity prediction of lower cretaceous unconventional resource play, south Indus Basin, Pakistan, using the seismic spectral decomposition technique | |
| CN105116449B (en) | A kind of recognition methods of weak reflection reservoir | |
| Lu et al. | Prestack inversion identification of organic reef gas reservoirs of Permian Changxing Formation in Damaoping area, Sichuan Basin, SW China | |
| Behrens et al. | 4D seismic monitoring of water influx at Bay Marchand: the practical use of 4D in an imperfect world | |
| CN114462237A (en) | Shale oil gas dessert prediction method | |
| CN111257933B (en) | Novel method for predicting oil and gas reservoir based on low-frequency shadow phenomenon | |
| Cao et al. | New method for characterizing internal structure of fault-karst reservoirs and analysis on acidizing fracturing effect: A case study in HLHT oilfield, Tarim Basin, NW China | |
| Abdolahi et al. | Identification and modeling of the hydrocarbon-bearing Ghar sand using seismic attributes, wireline logs and core information, a case study on Asmari Formation in Hendijan Field, southwest part of Iran | |
| CN111610560A (en) | Oil gas prediction method based on seismic longitudinal frequency spectrum time shift | |
| CN110967742A (en) | Porosity inversion method and system | |
| CN108983288B (en) | Oil-water identification method based on time-frequency spectrum image characteristic analysis | |
| Naseer et al. | Seismic attributes and spectral decomposition-based inverted porosity-constrained simulations for appraisal of shallow-marine lower-Cretaceous sequences of Miano gas field, Southern Pakistan | |
| Strecker et al. | Seismic attribute analysis in hydrothermal dolomite, Devonian slave point formation, Northeast British Columbia, Canada | |
| US11808909B2 (en) | System and method for predicting fluid type and thermal maturity | |
| RU2206911C2 (en) | Process of search, prospecting, examination of deposit of mineral wealth and of construction of its model | |
| CN113640873B (en) | Sandstone uranium ore pre-stack earthquake prediction method and device | |
| CN113495293B (en) | Reservoir fluid prediction method and device | |
| CN109507725B (en) | Method and system for predicting seismic attributes of effective reservoirs in sand-rich intervals | |
| RU2225020C1 (en) | Method of geophysical prospecting to determine oil productivity of fractured argillacous collectors in space between wells | |
| Shykhaliyev et al. | Pre-drill overpressure prediction in the South Caspian Basin using seismic data | |
| Liu et al. | Seismic integrated study for offshore deep-and thin-stratum characterization: A case study from the Enping sag within the Pearl River Mouth Basin | |
| Naseer et al. | Seismic frequency controls to characterize the lower-cretaceous incised-valley system, Indus Basin, SW Pakistan: Spectral decomposition as a direct hydrocarbon indicator | |
| Feroz | Integration of microseismic and time-lapse seismic data with application to a heavy oil reservoir |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200901 |
|
| RJ01 | Rejection of invention patent application after publication |