(3) Oil and gas detection methods

Finding sand body does not mean finding oil and gas. The purpose of exploration is to find oil and gas rather than sand bodies. How to judge whether the sand body contains oil and gas is the key to improve the success rate of drilling. Based on the statistical analysis of hundreds of exploration wells and development wells in Feiyantan area, through fine reservoir calibration, it is found that the oil and gas content of sedimentary microfacies in different types of rivers is quite different. Generally, the main channel and oxbow lake microfacies are characterized by rich provenance, strong hydrodynamic conditions, moderate grain size of sandstone, relatively good storage and permeability conditions and high oil grade. The seismic characteristics are "strong trough, low frequency and pull-down phenomenon", which are distributed in a curved strip shape on the plane. For example, the wells in the130 "S" shaped river channel are all industrialized. However, the riverbank, crevasse fan and flood plain sedimentary reservoirs are slightly poor in physical properties and oil content, such as Cheng 13 1 well. The above phenomenon shows the complexity of sandstone reservoir formation and the necessity of oil and gas prediction.

Figure 8-27 Prediction Diagram of Porosity and Permeability of Guantao Formation 14+5 in Feiyantan Area (red high value area)

1. Forward modeling the relationship between sandstone amplitude and thickness, oil-bearing property and sedimentary facies.

From the statistical scatter plot of sand layer thickness and amplitude in Feiyantan Oilfield, it looks chaotic on the surface, and there is no ideal linear relationship between amplitude and thickness within the theoretical tuning thickness range, but the overall trend is that amplitude increases with the increase of formation thickness. After careful analysis, it is found that these scattered points are four oil-water zones. In each band, the trend of amplitude increasing linearly with thickness is very obvious. We believe that the above phenomenon is mainly caused by the velocity difference of sand bodies with different sedimentary facies and different oil-bearing properties. Because from the relationship between speed and amplitude, speed and frequency, speed and amplitude have obvious positive correlation, while speed and frequency have negative correlation characteristics.

In order to further explore the relationship between sandstone amplitude and thickness, oil-bearing property and sedimentary facies, the ideal model is analyzed. A rhombic geological model is designed. The velocities of non-river oil sands, non-river water sands, river oil sands and river water sands are 2450 m/s, 2500 m/s, 2550 m/s and 2600 m/s respectively, and the velocity of mudstone is 2200 m/s for forward convolution, and the corresponding amplitude parameters are extracted for comparative study. It is found that the thickness and amplitude of channel water-bearing sandstone, channel oil-bearing sandstone, non-channel water sand and non-channel oil sand have a typical linear relationship within the range of tuning thickness, showing four obvious bands (Figure 8-28). The linear relationship between thickness and amplitude can be expressed as:

H = K 1* Am + K2

Where: K 1 and K2 are constants; H is the thickness; Am is amplitude.

From the comparison, the sandstone thickness increases by 200 ~ 240 for every 5 m of the same sedimentary subfacies with the same property. The amplitude of sandstone water layer with the same thickness and sedimentary subfacies is higher than that of oil layer 100 ~ 120, which is equivalent to the increase of sandstone thickness with the same property1.5 ~ 2.5m. The amplitude of channel sandstone is 220 ~ 240 higher than that of non-channel sandstone with the same property and sand layer thickness. From this point of view, the amplitude of sandstone reservoir in the upper Guantao Formation is closely related to sand thickness, sedimentary facies and oil-bearing property. These factors control the variation of amplitude to varying degrees, but sedimentary subfacies and sand thickness contribute the most to the amplitude.

2. Gas reservoir prediction

The gas reservoir has the characteristics of bright spots, but the intensity of bright spots in different sedimentary subfacies is different. By classifying the bright spots in the work area and forward analyzing the bright spot boundary and gas-water boundary, the distribution range of gas reservoirs can be well determined.

(1) bright spot classification and sedimentary subfacies division

Based on the statistics of seismic gas layer thickness, depth, velocity, natural potential characteristics and gas layer amplitude of more than 20 wells in this area, the different relationship curves between gas layer thickness and amplitude of bright spots in river subfacies and non-river subfacies in this area are fitted, and the relative amplitude zoning threshold of class I and II bright spots is 7000, and the relative amplitude thresholds of gas-bearing bright spots in river subfacies and non-river subfacies are 3000 and 3000.

According to the statistics of amplitude and velocity of known wells in this area, it can be seen that the interval velocity of non-channel subfacies is relatively high and the amplitude value is relatively low, while the interval velocity of channel subfacies is relatively low and the amplitude value is relatively high. Based on the actual statistical data, we designed the forward modeling of gas-sand bodies in channel subfacies and non-channel subfacies. By extracting the amplitude parameters of seismic response and fitting the relationship curve with the corresponding gas reservoir thickness, it can be seen that the variation law of amplitude and thickness is consistent with the variation law of reservoir thickness inversed by actual well data, which proves that the method of inversing reservoir thickness by using well data is correct.

From the amplitude and thickness fitting curves of channel subfacies and non-channel subfacies, it can also be seen that the second bright spot includes two sedimentary subfacies: channel subfacies and non-channel subfacies. Only by distinguishing the correlation can we ensure the accuracy of gas reservoir thickness inversion and reserve calculation. For this reason, we mainly divide the bright spots according to their shapes: the banded bright spots deposited in the river channel and the ox yoke bright spots formed in the abandoned river channel belong to the river subfacies; Potato-shaped bright spots deposited on the floodplain and flask-shaped bright spots formed by crevasse fans belong to non-channel subfacies.

To sum up, each bright spot is not only divided into ⅰ and ⅱ categories, but also into sedimentary subfacies, which lays a necessary foundation for the accuracy of gas layer thickness inversion of bright spots in different sedimentary subfacies and the reliability of bright spot reserves calculation.

(2) bright spot boundary and gas-water boundary division

1) Determination of the boundary of bright spots. It can be seen from the model analysis and actual well statistics that the amplitude and thickness curves of channel subfacies and non-channel subfacies are obviously divided, so when determining the bright spot boundary, the bright spot boundary thresholds of channel subfacies and non-channel subfacies are different. Therefore, according to the statistical law of real wells, it is determined that the range where the amplitude of bright spots in river subfacies is greater than 3000 and that in non-river subfacies is greater than 2000 is the gas-bearing range of bright spots.

Figure 8-28 Relationship between amplitude and thickness, sedimentary facies and oil-bearing property of channel sand body

Figure 8-29 Relationship between Gas Layer Thickness and Amplitude in Feiyantan Area

2) Analysis of bright spot gas-water boundary model. There are two kinds of reservoirs in Feiyantan gas field: pure gas and gas-water sandstone. Can the gas-water boundary be determined by seismic data? Therefore, according to the actual geological data in this area, we designed the lens model of gas-water sandstone, extracted the amplitude value from its seismic response, and made the curve of thickness and amplitude change. It can be seen that the gas-water boundary will only appear when the thickness of the lens body is greater than 36 m (λ/2) (Figure 8-30). Because the sandstone in this area is deposited by meandering river and its thickness is generally less than 36 m, it is determined that this area is gas-water sandstone gas-water.

Figure 8-30 Analysis of Bright Spot Gas-water Boundary Model

3. Reservoir exploration

(1) instantaneous wavelet absorption analysis technology

In the process of underground seismic wave propagation, in addition to the overall energy attenuation, the frequency components are also attenuated to varying degrees with different media. Due to the viscosity effect of the medium, the high-frequency components of seismic waves will be attenuated in the propagation process, especially in the loose medium or the medium with gas in the pores, the high-frequency energy of seismic waves will be attenuated quickly. Therefore, the attenuation law of high-frequency energy in the process of seismic wave propagation can be used for the analysis of rock type, porosity and fluid type. Absorption analysis uses this principle to analyze the oil-bearing and gas-bearing characteristics of reservoirs (Figure 8-3 1). In practical application, Metalink system can be used to analyze the oil-gas bearing property of reservoirs. Metalink system is an instantaneous wavelet absorption analysis software system, which uses seismic amplitude information to predict oil and gas reservoirs. Amplitude-preserving processing and oil and gas detection are two key technologies. Due to the limitation of data quality and computing power, the traditional seismic data processing methods use too many digital assumptions and constraints, which greatly improves the relative relationship between the frequency spectrum and amplitude of seismic data, so ideal amplitude-preserving results cannot be obtained. In order to ensure the accuracy of the extracted seismic information, Metalink system firstly processes the seismic data with high resolution, high signal-to-noise ratio and high fidelity, so as to keep the relative amplitude, frequency and waveform of the seismic information. On this basis, the energy absorption analysis based on wavelet is carried out, that is, the seismic wavelet and reflection coefficient sequence are separated on the re-matched spectrum, and the seismic wavelet with time-varying and space-varying energy is obtained, and then the vertical distribution law of instantaneous wavelet energy attenuation is obtained, so as to eliminate the interference of strong reflection and accurately analyze the absorption anomalies of oil-bearing and gas-bearing layers in the post-stack data (Wang Hongyu, 2007).

Fig. 8-3 1 principle of instantaneous wavelet absorption analysis (according to Wang Hongyu, 2007)

The main modules of application of instantaneous wavelet absorption analysis technology include the following aspects:

1)PID inverse convolution. In the spectrum of seismic records, wavelet is equivalent to smooth component, while reflection coefficient and noise are "glitches" in the spectrum. Seismic records can be expressed as the convolution of wavelet and reflection coefficient. The spectrum of seismic record is the product of wavelet spectrum and reflection coefficient spectrum, that is, S (f) = w (f) RC (f). After logarithm, S'(f)= W'(f)+Rc'(f) is transformed into time domain (re-matched spectrum) by inverse Fourier transform. Wavelet and reflection coefficient are located at the near time end and far time end of the re-matched spectrum, so a time domain filter can be designed to separate time-varying and space-varying wavelet. Wavelet contains all kinds of amplitude and phase information in the process of seismic wave propagation. Deconvolution can eliminate the influence of multiple waves and non-surface consistency, and can also achieve the effect of spectral balance for post-stack data (Wang Hongyu, 2007).

2)PMO phase dynamic correction. A method for phase leveling of gathers without input speed. Firstly, the anti-cosine of amplitude spectrum and phase spectrum of seismic data is studied.

Petroleum Geology and Exploration Technology of Guantao Formation in Northern Jiyang Depression

Petroleum Geology and Exploration Technology of Guantao Formation in Northern Jiyang Depression

It can be seen that only the phase spectrum contains the information of earthquake travel time. In this way, phase equalization can be achieved by using the phase spectrum of the near offset trace instead of the far distance, while preserving the amplitude spectrum of each trace in the gather. Compared with amplitude-preserving processing, PMO can flatten the non-hyperbolic phase.

3) instantaneous wavelet absorption analysis of 3)WEA. Seismic record is the convolution of seismic wavelet and reflection coefficient, which is the combination of stratigraphic framework sequence and does not represent the absorption characteristics of strata. Because the reflection coefficient interferes with the seismic spectrum, the result of absorption analysis is bound to be influenced by the reflection coefficient, resulting in the phenomenon of "false bright spot", that is, strong reflection leads to strong absorption, which greatly restricts the practical application effect of absorption analysis. The interference of reflection coefficient makes absorption analysis greatly influenced by the intensity of reflection amplitude, and seismic wavelet is a comprehensive carrier of seismic wave being filtered by the earth during its propagation. Robust absorption analysis should be based on wavelet frequency attenuation analysis. WEA uses this principle to calculate the seismic wavelet in the sliding time window of seismic trace records, and interpolates the zero-time trace with the whole trace information to obtain the reliable seismic spectrum in the small window. Then the amplitude spectrum of wavelet is extracted in the re-matched spectral domain by using PID inverse convolution wavelet extraction technology, and the high-frequency energy attenuation curvature on the spectrum is fitted. Because the calculation process is small window sliding calculation, a new wavelet high frequency energy attenuation curvature curve can be obtained. In order to eliminate the influence of attenuation caused by geodetic filtering with the increase of buried depth, it is necessary to separate the residual attenuation curvature output by trend analysis to form a new absorption prediction trace. In this way, the anomaly after removing the natural absorption background can better reflect the absorption and attenuation of the target reservoir, and is not limited by the buried depth of the formation.

Of course, any geophysical analysis method will be affected by the signal-to-noise ratio, and WEA is no exception, so it needs careful analysis in areas with low signal-to-noise ratio. As for the resolution, due to the small window sliding analysis, we get rid of the restriction of λ/ 4, but it is still limited by the seismic sampling rate. It can be seen from the implementation process that WEA makes full use of seismic information and does not need the constraint of logging data. However, the absorption coefficient calculated by WEA is a relative value, so gas reservoirs cannot be identified by numerical values. This process requires calibration of well information. WEA reflects the relationship between strength and weakness. The area with known gas well location can be regarded as gas reservoir or oil reservoir, the area with known dry well location can be regarded as gas reservoir or oil reservoir, and the area with known dry well location can be regarded as non-gas reservoir or oil reservoir (Wang Hongyu, 2007).

Example: instantaneous wavelet analysis of feiyantanting 14+5 sand group. On the basis of seismic information analysis, the parameters of instantaneous wavelet absorption analysis are determined, including different frequencies, wavelet length, sliding time window size and absorption analysis type. On this basis, firstly, the parameters and effects of seismic profiles of oil and gas wells are tested. Metalink system can directly analyze the instantaneous wavelet absorption of three-dimensional seismic data, but it takes a long time because of the large amount of data. Therefore, along the survey line direction and trace direction, with the interval of 10 line and 10 trace, 3D seismic data are extracted into 2D seismic data, which are analyzed by instantaneous wavelet absorption with the same processing parameters as the above-mentioned cross-well profile, and then the processing results (segy format file) are loaded into other seismic attribute systems (such as MDI) for display, and the absorption attributes along the layer are extracted (the profile itself is absorption) Compared with actual drilling, this technology can well predict the plane distribution of oil reservoirs (Figure 8-32 and Figure 8-33), and the coincidence rate reaches 80%.

(2) Instantaneous frequency method

Instantaneous frequency method is to judge whether the sand body contains oil by extracting instantaneous frequency parameters. In Feiyantan area, the instantaneous frequency parameters are extracted, and the statistics of several wells show that the instantaneous frequency is less than 34Hz, which is generally an oil-bearing area, and the instantaneous frequency is greater than 40Hz, which is an oil-water transition zone. In Feiyantan area, most sand body oil and gas identification wells deployed according to instantaneous frequency are consistent with drilling conditions (Figure 8-34). It can be concluded that the different fluids in the sand body cause the selective absorption of seismic wave frequency, and the seismic profile shows that the sand body is mainly composed of low frequency components after oil content and high frequency components after water content. From the application situation, this method is suitable for judging whether river sand bodies contain oil and gas.

Figure 8-32 Instantaneous Wavelet Absorption Analysis Profile

Figure 8-33 Instantaneous Wavelet Absorption Analysis Diagram of Guantao Formation 14+5 Sand Layer

Figure 8-34 Relationship between Instantaneous Frequency and Sand Body in Feiyantan Area