Multi-well logging evaluation is a comprehensive reservoir evaluation technology developed in recent years. Based on the analysis of logging data and coring data, the four-property relationship is established, the reservoir parameters are calculated, the variation law of reservoir parameters and the corresponding relationship of sedimentary microfacies are analyzed, and an accurate geological model is established.
Multi-well evaluation of reservoir parameters; Sedimentary microfacies
The well pattern density of the first member of Zaobeikong reaches 1.75m well spacing, and the well pattern is highly controlled, with 6 coring wells. The data of coring thin section analysis, physical property analysis, particle size analysis, mercury injection analysis, oil-gas-water analysis and oil test and production test are very rich, which provides a solid foundation for multi-well evaluation of logging.
First, the establishment of rock volume model
Rock volume model is a high generalization of rock composition and pore distribution in this area, and it is also the main geological basis for multi-well reservoir evaluation by logging. According to the statistical analysis of 206 core slices in this area, the rock composition of the first member of Zaoeryou Formation in Zaobeikong is mainly feldspar sandstone and feldspathic lithic sandstone, and its mineral composition is as follows:
Timely+flint: 22.0% ~ 49.0%, with an average of 35.62%;
Feldspar (including orthoclase and plagioclase): orthoclase, 8.0% ~ 35.0%, with an average of 20.59%; Plagioclase, 12.0% ~ 29.0%, averaging 21.72%;
Debris: 8.0% ~ 38.0%, with an average of 22.07%, of which igneous debris accounts for 16.23%.
The total amount of debris composed of the above three elements accounts for 85.5% of the rock skeleton.
Cement content: 14.5%, including argillaceous content of 8.34% and calcium content of 6.16%;
Porosity: 9.0% ~ 45.0%, with an average of 24.6%;
Converted into absolute volume percentage according to unit volume, the porosity is: v φ = 24.6%;
Skeleton: Vma=75.4%, of which: Yingshi+flint, 22.96%; Feldspar, 27.28%; Cutting,14.23%; Cementite, 10.93% (containing 6.28% argillaceous).
According to the core analysis, the shale content in this area is less (6.28%), so the geological body model in this area can be established as a pure sandstone model. Its main components, such as quartz, flint and feldspar, are similar in density, and the components are also silicate minerals. Igneous rock cuttings are mainly intermediate andesite and basalt cuttings, and the acoustic time difference is between 160 ~ 200μ s/m, and the corresponding tma acoustic time difference is180μ s/m. According to the analysis of oil, gas and water properties in the first member of the northern space, the fluid time difference is almost gas-free, and the original oil-gas ratio is very low, so the fluid time difference is desirable. TF = 620μ s/m. In terms of rock electrical coefficient, the original rock electrical coefficient of the first member of Zaobeikong can meet the local requirements for accurate oil saturation, so it is still selected.
Coefficient: a = b =1;
Cementation index: m = 2；;
Saturation index: n= 1.348.
Study on the relationship between sex and sex.
After core analysis, accurate homing and logging data processing and interpretation, the key to multi-well logging reservoir evaluation is to accurately determine the four-property relationship.
1. Relationship between rocks and physical properties
According to the data of core physical properties and particle size analysis, there are mainly porosity (φ), permeability (K), shale content (Vsh), median particle size (Md) and irreducible water saturation (Swi). By determining their relationships, namely φ-VSH, φ-MD, VSH-MD, SWI-φ, SWI-VSS.
MD =-0. 1 168437 ln vsh-43.68 1989
R=0.80833，n=290
The correlation of regression is low, which shows that the influence between these parameters is not single, but the result of the joint action of multiple parameters. For example, porosity is affected by median particle size and shale content, while irreducible water saturation is related to porosity, shale content and median particle size. The factors affecting permeability are porosity, median particle size, shale content and irreducible water saturation.
Therefore, on the basis of single correlation analysis, multiple regression analysis is mainly carried out, and the effects of porosity, median particle size and shale content on bound water saturation and permeability are studied in detail, and error analysis is carried out.
(1) The relationship between irreducible water saturation and porosity and shale content is as follows:
LG swi = 2.904 13+0.4238 LG vsh- 1.357473 LGφ
R=0.8845，F= 136.6027
(2) The relationship between irreducible water saturation and porosity and median particle size:
lgSwi = 3.772865- 1.782877 LGφ-0.2654393 lgmd
R=0.87 139，F= 12 1.56096
Through multiple regression analysis, the above two formulas show more clearly that the irreducible water saturation is controlled by many factors. The error of irreducible water saturation calculated by two-factor regression is small, and the correlation coefficient is obviously higher than that of single comparison. The basic change law obtained is similar to that of single correlation. The irreducible water saturation decreases with the increase of porosity and median particle size, and increases with the increase of shale content.
(3) The relationship between permeability and porosity and shale content is as follows:
Jujube-Ⅱ oil group:
lgK = 2.534756+0.045664 LGφ—0.053867 lgvsh
n= 135，F=236，R=0.884 15
Zao-Ⅳ oil group:
lgK = 0.09954+0. 127 1 1lgφ—0.05 1258 lgvsh
n=77，F= 123，R=0.87660
Kong Yi group (jujube-Ⅱ+jujube-Ⅳ):
lgK = 1.026956+0.0947 13lgφ-0.049306 lgvsh
n=2 12，F=340，R=0.875 1
(4) The relationship between permeability and porosity and median particle size is as follows:
Jujube-Ⅱ oil group:
lgK = 0.34 1763+2.988509 LGφ+2.078932 lgmd
R=0.80382，F= 120.5078
Zao-Ⅳ oil group:
lgK =-5.545305+6.297524 LGGφ+0.833964 lgmd
R=0.75 18，F=45.5242
The above types show that there are many factors affecting permeability, which increase with the increase of porosity and median particle size and decrease with the increase of shale content.
2. The relationship between lithology, physical properties and electrical properties
Although core analysis can accurately and truly reflect the situation of underground reservoirs, it can only reflect the situation of individual points of reservoirs due to the lack of coring wells. Although logging information can widely reflect the characteristics of underground reservoirs, it only reflects indirect geological information, so it is very important to effectively establish the relationship between lithology, physical properties and electrical properties for reservoir evaluation and research. The spontaneous potential in acoustic induction series logging information reflects the characteristics of lithology change, and acoustic wave (? T) Reflect the physical properties of rocks. Inductive resistivity and flushed zone resistivity reflect the fluid properties of the original stratum and flushed zone respectively. Comprehensive application of various curves and parameters can reflect the seepage characteristics of strata. Therefore, the conversion relationship between logging information and geological analysis information can be established based on core analysis data.
(1) porosity (φ) and acoustic time difference (? T) relationship
Through the statistical analysis of the data of 33 layers, the porosity has the following relationship with the acoustic time difference (Figure 1).
Figure 1 Relationship between porosity and acoustic time difference
φ=0. 17473397? t-29.38386 1 15
n=33，R=0.9302 1
The above formula shows φ and? T is a linear relationship, and the porosity regression value is in good agreement with the core analysis value. Considering the correction of formation compaction, the porosity calculation formula of pure sandstone model (that is, Willie formula)
Application of reservoir description technology in the south area of Huanghua depression
Cp= 1.635—0.002 13H
Where:? T—— acoustic logging value;
TMA-bone sound wave time difference. TMA = 180μs/m；
Tf—— Time difference of fluid acoustic wave. TF = 620μs/m；
H—— Depth (m).
The porosity calculated by the formula is in good agreement with the regression porosity and core analysis porosity, which shows that the regression formula is in good agreement with the porosity calculation formula, and the error is less than 65438 0.0%.
(2) Relationship between shale content and relative value of spontaneous potential.
Based on the data of 32 layers, the relationship between shale content and spontaneous potential (? SP) (figure 2)
lnVsh=3.9962642×？ SP+ 1.07998997
n=32，R=0.9955
The regression value of shale content is in good agreement with the core analysis value.
Fig. 2 Relationship between shale content and relative value of spontaneous potential
The empirical formula for calculating shale content is:
Application of reservoir description technology in the south area of Huanghua depression
Where: gcur-empirical constant, taking GCUR = 3.7；;
SP-the relative value of spontaneous potential;
SP- spontaneous potential logging value;
Gmn 3- the minimum value of spontaneous potential;
GMX3-the maximum value of spontaneous potential.
The shale content calculated by this formula is consistent with the core analysis value and regression value, and the error between them is very small, less than 65438 0.0%.
(3) Relationship between permeability and logging response
Due to many factors affecting permeability, it is difficult to obtain accurate permeability in logging interpretation. According to the core analysis, the factors affecting the permeability of the first member of Zaobei hole are porosity, argillaceous content, median particle size and so on. There is a good correlation between shale content and median particle size, so porosity and shale content can be used to estimate permeability.
The relationship between K and φ, Vsh is established by multiple regression of porosity and shale content in core analysis.
Jujube-Ⅱ: LGK =1.51785+0.081914lgφ-0.043804lgvsh.
n= 16，F= 10.722，R=0.789
Jujube-Ⅳ: lgk = 0.864710+0.01252lgφ-0.024958lgvsh.
n= 16，F=2 1.80，R=0.87770
Jujube-Ⅱ+Jujube-Ⅳ: LGK =1.108244+0.099686 LG φ-0.05572 LG VSH.
n=32，F= 103.5，R=0.93654
The above relationship shows that K has a good correlation with φ and Vsh. On this basis, according to the geological information reflected by logging, the acoustic time difference (? T) Relative value of spontaneous potential (? SP) Establish the permeability response equation as follows:
Jujube-Ⅱ oil group:
lgK =-3 1.579930+ 14.38064×LG？ t-0.77 1037×lg( 100？ SP)
n= 16，F= 16.69756，R=0.8484 1
Zao-Ⅳ oil group:
lgK =- 12.77963+7.983244×LG？ t-2.7969 1 1×LG( 100？ SP)
n= 16，F=26.3466，R=0.8956 1
Hole 1 section (Zao Ⅱ+Zao Ⅳ oil group):
lgK =-27.2 1005+ 13.4 1356 LG？ t-2. 124 107 LG( 100？ SP)
n=32，F= 100.04，R=0.9348
Judging from the error analysis of regression calculation, it is better to calculate Zao-Ⅱ and Zao-Ⅳ oil groups separately, and the relative error between calculated values and core analysis data is basically less than 0.4%.
(4) Relationship between oil saturation and resistivity
There are two sealed coring wells in the first section of Zaobeikong, namely Zaojian-1 and Zaojian -2. The oil saturation of core analysis basically reflects the original oil saturation. In logging information, the resistivity of deep exploration directly reflects the fluid properties in pores. For pure sandstone model, So-Rt relation can be expressed by Archie formula. If the electrical parameters in northern Zaobei area are A = B = 1, M = 2, N = 1.348, the theoretical formula for calculating water saturation is as follows.
Application of reservoir description technology in the south area of Huanghua depression
In a sealed coring well, we studied the relationship between water saturation and induced resistivity (Rt) in five formations with high sealing rate:
Sw=405.77923725( 1/Rt)
n=5，R=0.94955，Rt∈[6.0， 10.0]
The above formula shows that Sw is closely related to RT, and it decreases with the increase of RT. The theoretical calculation value and regression calculation value are very close to the core analysis value, with relative error less than 15% and absolute error less than 6.0%. However, due to the limitation of the range of sample points, the regression formula cannot be used to predict the oil saturation of the first member of Zaobei hole, because the resistivity of the first member of hole is generally between 3.0 and 6.0 Ω m. Therefore, the sampling points are not representative and cannot reflect the characteristics of a certain section of the borehole.
The study on the relationship between lithology, physical properties, oil-bearing property and electrical property shows that the shale content, porosity and oil saturation can all be calculated by empirical formula, because the calculated value and regression value of empirical formula are very close to that of core analysis, while Timur formula is not suitable for permeability calculation, and the response equation obtained by multiple regression analysis has small error.
3. Establish logging interpretation model and calculate reservoir parameters.
Through the study of the above four relationships, the logging interpretation model suitable for the first member of Zaobeikong is as follows.
Porosity:
Mud content:
Application of reservoir description technology in the south area of Huanghua depression
Application of reservoir description technology in the south area of Huanghua depression
Application of reservoir description technology in the south area of Huanghua depression
Permeability:
Jujube-Ⅱ oil group:
lgK =-3 1.579930+ 14.38064×LG？ t-0.77 1037×lg( 100？ SP)
Zao-Ⅳ oil group:
lgK =- 12.77963+7.983244×LG？ t-2.7969 1 1×LG( 100？ SP)
Hole 1:
lgK =-27.2 1005+ 13.4 1356×LG？ t-2. 124 107×LG( 100？ SP)
Irreducible water saturation;
LG swi = 2.904 13+0.4238×LG vsh- 1.357479×LGφ
Oil saturation (Archie formula):
Application of reservoir description technology in the south area of Huanghua depression
On the basis of standardization of logging data, processing and interpretation, comprehensive utilization of logging and oil testing data, reasonable selection of parameters, calculation of reservoir parameters, distinction between oil, gas and water layers, and verification of the accuracy of the obtained parameters through key wells. By comparing the superposition of core analysis data of key wells with corresponding logging calculation parameters, it is shown that the two values are close and the error is very small, which shows that the above logging interpretation model meets the requirements of obtaining geological parameters. According to the coincidence analysis of oil, gas and water layers, the coincidence rate of oil, gas and water layers discrimination is above 90%, and the coincidence degree is high.
Through multi-well logging interpretation, the reservoir parameters such as sandstone thickness, shale content, porosity, permeability, oil saturation and effective thickness of single sand layer are obtained in the form of results table, and the distribution of oil, gas and water on single well profile is obtained.
Fourthly, the distribution law of reservoir parameters
Using the reservoir parameters interpreted by logging, the plane contour map of each oil group and small layer is drawn to study its plane distribution law. Taking the fourth sub-layer of Zaoer oil formation as an example, its distribution characteristics are expounded.
The fourth sub-layer of Zaoer Oil Formation is distributed in the northeast direction, with the formation thickness of about 10 ~ 20m, and the sandstone thickness varies from 0 ~ 10~20m, with an average thickness of 5.71m.. River pillars obviously bifurcate and merge, and sandstone pinches out in some areas (Figure 3).
The shale content ranges from 7.28% to 37.19%, with an average of 16.45%, and its distribution characteristics are basically consistent with sandstone. Where the sandstone is thick, the argillaceous content is generally less than 20%. Individual well points are abnormal, which is related to river diversion, migration and single sand accumulation in small layers (Figure 4).
Porosity ranges from 18.6% to 29.36%, with an average of 24.87%. Where sandstone develops, the porosity is greater than 24%. The permeability ranges from 312×10-3 to 4,800×10-3 μ m2, with an average of 2,058×10-3 μ m2 (Figures 5 and 6).
The oil layers in the 4th subzone of Zaoer Oil Formation are widely distributed, with oil saturation of 37.7 1%-82. 14%, with an average of 6 1.47%, maximum effective thickness of10.8m, with an average of 4.1.0m ..
By describing the characteristics of reservoir parameters of oil groups and small layers layer by layer, the distribution law of reservoir parameters is summarized as follows.
1. The shape and distribution of sand bodies are controlled by sedimentary microfacies.
The first member of Zaobeikong is alluvial fan deposit, and the reservoir sand body is mainly braided channel sand body, followed by thin sand deposited by overflow dam. Small-layer channel sand bodies are distributed in strips, and the thickness is generally greater than 4m. The distribution and extension direction of sand bodies are consistent with the direction of ancient water flow, showing a northeast trend. In the northeast of the study area, the river form is obvious, and the phenomenon of confluence and bifurcation of rivers is common in the middle and southwest, which embodies the characteristics of frequent river diversion and rapid migration. The cross section of channel sand body is lenticular, with rapid change of lateral thickness and poor connectivity. River sand bodies extend far along the direction of water flow, but the connectivity of sand bodies is also poor due to the cutting of faults. The channel width is between 400 ~ 1000 m, and the sand body in the channel moves and changes rapidly relative to each sublayer. Zaoer oil formation was deposited in the period of alluvial fan from prosperity to decline. It can be seen that during the deposition period of the 4th, 5th and 6th layers, the distribution position of river channels is relatively stable, and from the 3rd layer to the 1 layer, there are frequent diversions and migrations between rivers. The thickness of 1 and 2 layers is large and the ratio of sand to mud is small, which indicates that they were deposited during the decline of alluvial fans. In Zaoer Oil Formation, the 4th, 5th and 6th layers of sandstone are the most developed, while the 3rd, 7th layers 1 and 2nd layers are poor.
2. The silt content is controlled by the development degree of sand body.
The distribution characteristics of argillaceous content are basically consistent with sandstone, and the argillaceous content in sandstone development area is small, generally less than 20%, reflecting that the deposit is braided river deposit with strong hydrodynamic force. However, where sandstone is undeveloped, the argillaceous content is relatively large, generally above 20%, which is manifested as river bank overflow or inter-river depression deposition. The variation of shale content in small layers is consistent with the development characteristics of sandstone, with little shale content in layers 4, 5 and 6 and large shale content in layers 3 and 7, 1, 2. Some wells are abnormal, such as sandstone with large thickness and high shale content, or sandstone with small thickness and low shale content, which is related to the distribution of single sand layer in small layers and the overlapping of thin layers.
Fig. 3 Isogram of thickness of sandstone in layer 4 of Zao 1 Oil Formation
3. Reservoir physical properties are controlled by sand microfacies and diagenesis.
The distribution of reservoir porosity and permeability is related to sandstone thickness, argillaceous content, buried depth of strata and diagenesis in the later stage. Zaoer oil formation is a reservoir with high porosity and ultra-high permeability, and sandstone is developed, with porosity generally greater than 22.0% ~ 24.0% and permeability greater than 1 1,000×10-3 μ m2, but it is lower than this value where sandstone is not developed. According to the seven sub-layers of Zaoer oil formation, the physical properties tend to get worse from shallow to deep, and the porosity and permeability of sub-layers 3, 4 and 5 are relatively good. However, 1 and 2 sublayers have large shale content and relatively large porosity and permeability. This is related to shallow burial, high shale content, easy to cause borehole diameter expansion, large acoustic time difference and large calculated porosity and permeability.
Fig. 4 Isogram of Mud Content in Layer 4 of Zaoer Oil Formation
4. Oil bearing property is controlled by lithology and structure.
Zao-Ⅱ oil reservoir is distributed in the graben nose structure inclined to the southwest, and there is no oil in the area outside Zao-126 1 well at the inclined end. The oil-water boundary line is parallel to the structural contour line. The plugging of faults leads to great differences in oil-bearing properties between fault blocks, some of which do not contain oil, and other fault blocks have different oil-water interfaces and oil column heights. Under the same lithologic conditions, the oil saturation and effective thickness in the high part of the structure are mostly related to the oil-water gravity differentiation. Above the oil-water interface, the distribution of oil layers is controlled by lithology, and the places where river sand bodies develop have high oil saturation and large effective thickness. Where the lithology is poor, even in the high part of the structure, the oil content is poor. Among the seven sublayers of Zao-2 oil formation, the sublayers 3, 4, 5 and 6 have good oil-bearing properties, and the oil layers are stacked and contiguous, with a distribution range greater than 60.0%. At a small level, the distribution range of oil layers is less than 50.0%; 1 and 2 layers have poor oil-bearing property, and the oil-bearing range is less than 40.0%.
Fig. 5 Isogram of Porosity in Layer 4 of Zaoer Oil Formation
5. Relationship between reservoir properties and sedimentary microfacies
Taking the fourth layer of Zaoer oil formation as an example, the lithology, reservoir properties, oil content and reservoir types of four microfacies sand bodies of alluvial fan are explained.
Braided main channel microfacies: the thickness of sandstone is generally more than 6m, the argillaceous content is low 10% ~ 16%, the porosity is 24% ~ 30%, and the permeability is high1000×10-3 ~ 4,000×/kloc-0. Braided channel microfacies: sandstone thickness is 4 ~ 6m, low shale content 12% ~ 20%, porosity is 20% ~ 24%, and permeability1000×10-3 ~ 2000×10-3 μ m2. When there is oil, the saturation reaches 50% ~ 60%, and the effective thickness is 2 ~ 4m, which is also lower than the main channel sand body. Comprehensive evaluation shows that it is a good reservoir.
Fig. 6 Permeability Isogram of Layer 4 of Zaoer Oil Formation
Inter-channel microfacies: generally, there are more mud and less sand, and there are channel sand body edges and thin sand bodies. The thickness of sandstone is generally less than 3m, and the argillaceous content is 20% ~ 30%. The porosity is the same as that in the same channel, and the permeability is low, ranging from100 to 500×10-3 μ m2. When there is oil, the oil saturation is 39% ~ 60%. Comprehensive evaluation shows that the reservoir is poor.
Overflow microfacies: generally mudstone and argillaceous siltstone, mixed with thin sand, generally less than 1.0m in thickness, with argillaceous content higher than 30%, low porosity and permeability, poor lithology and physical properties, and generally non-reservoir.
Fig. 7 Isogram of Oil Saturation in Layer 4 of Zaoer Oil Formation
Reservoir evaluation of intransitive verbs
According to the types of reservoir lithology (sandstone thickness, shale content), physical properties (porosity, permeability) and oil-bearing property (oil saturation, effective thickness) delineated on the isoline map of reservoir parameters, and according to the average values of various parameters of each fault block, the parameters of each fault block in Zaoer oil formation are evaluated, and then the reservoir is comprehensively evaluated. The assessment conclusions are as follows:
Fig. 8 Equivalent diagram of effective thickness of four sub-layers of Zaoer oil formation
Zao Ⅱ oil group in the first member of Zaobeikong (1) is a reservoir with high porosity and ultra-high permeability. Among the seven sublayers of Zaoer oil formation, the lithology and physical properties of sublayers 4, 5 and 6 are good, while those of sublayers 3 and 7 are poor. The lithology of Zao Ⅲ oil group is better than that of Ⅱ oil group, but its physical properties are worse than that of Ⅱ oil group.
(2) Combined with comprehensive evaluation of oil-bearing property and lithology, the 4th, 5th and 6th layers of Zao-2 oil formation are good reservoirs; 3, 7 small grades, which are good reservoirs; 1 and layer 2 are the worst.
(3) In each fault block, there are three types of reservoirs in each sub-layer of Zao-2 oil formation. According to the comprehensive situation of each sub-layer, Zao 13, Zao 1256, Zao 7, Zao 125 1, Zao 2 and Zao.
refer to
(1) Ma Zheng. Interpretation of sedimentary environment by spontaneous potential logging curve. Petroleum and natural gas geology, 1982.
Qiu Yinan. Sedimentary basis of clastic reservoir. Beijing: Petroleum Industry Press, 1987.
Yong Shi and Hong. Comprehensive interpretation and digital processing of logging data. Beijing: Petroleum Industry Press, 1982.
(4) Editor-in-Chief of Petroleum Logging Branch of China Petroleum Institute. Application of logging in reservoir description. Beijing: Petroleum Industry Press, 1992.