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2D Seismic Exploration For The Coal Resources Survey
2D Seismic Exploration For The Coal Resources Survey 2D Seismic Exploration For The Coal Resources Survey
2D Seismic Exploration For The Coal Resources Survey 2D Seismic Exploration For The Coal Resources Survey
2D Seismic Exploration For The Coal Resources Survey 2D Seismic Exploration For The Coal Resources Survey

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2D Seismic Exploration For The Coal Resources Survey

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1. Introduction

Liulin Shixi Coalbed Methane Resources Exploration Project is located in the west of middle section of Hedong Coalfield, with an exploration area of 50.52km2. Four survey lines were arranged in a "tic-tac-toe" shape with a area of 5-8 km. In the exploration area, the highest elevation is 960.6m, the lowest elevation is 626.1m, and thus the height difference is 334.5m. There is big lateral change of the seismic and geological conditions of the superficial layer. Geological tasks require detecting the occurrence of sandstone layers in Liujiagou Formation, Upper Shihezi Formation, Lower Shihezi Formation and Shanxi Formation, main coal seams (No.4 and No.8 coal), Ordovician limestone and salt strata in Majiagou Formation, with a depth ranging from 280m to 3,200m.

2. Treatment Solution

The observation system with small track distance, large arrangement and high coverage times was designed to ensure the effective covering degree of the target strata with different burial depths, and the larger arrangement length was beneficial to pre-stack inversion later. In the process of data acquisition, digital geophones were used to ensure the effective reception of weak reflection signals, and large well depth, combined well and appropriate excitation dose were used to ensure the energy and resolution of the reflected waves.

The elevation of the highest point of the surface elevation was selected as the datum elevation for field static correction, and the wavelet matching technology was used to solve the superposition of single shot with different frequencies in the same direction, so as to ensure the signal-to-noise ratio, resolution and fidelity of the data. See Figure 1 for the time profile of the main standard reflected waves in the area.


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Figure 1: Main standard reflected waves in the area

The constrained sparse pulse inversion of acoustic impedance data volume established on the basis of constrained well data and seismic reflection coefficient wass used to predict the lithology, and AVO inversion was used to predict the gas-bearing property of "amplitude changes with offset" in pre-stack gathers. Finally, the resource-rich areas were predicted and analyzed according to the gas-bearing property and reservoir thickness. See Figure 2 for the lateral distribution of sand bodies in the area, and Figure 3 for the spatial distribution of sand bodies.

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Figure 2: Lateral distribution of the sand bodies in the area

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Figure 3: Spatial distribution of the sand bodies in the area

3. Work situation

4 survey lines with a total length of 58.02 km, 981 physical production points and 59 physical test points (thus a total of 1,040 physical points) were completed in the 2D seismic exploration. There were 981 production records, including 602 records of the grade A, with a grade A rate of 61.37%, 378 records of the grade B, with a Grade B rate of 38.53%, and one scrap record with a rejection rate of 0.1%. All test records were qualified.

4. Achieved accomplishment

The 2D seismic exploration achieved the following results: ① Foud out the buried depths and structural forms of the bottom boundaries of the main coal seam and the target layer in the exploration area; ② Foud out the change trend of the thickness of overburden, main coal seam, and sandstone, shale and salt rock layers in the target layer; ③ Predicted the gas-bearing property of reservoirs and resource-rich zones in the exploration area, and suggested the hole locations. See Figure 4 for a lithological prediction profile of the section 8 of Lower Shihezi Formation - Benxi Formation under the main survey line in the area.

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Fig. 4: Predicted lithologic thickness profile of the main survey Line (Section 8 - Benxi Formation)


5. FAQ

Q1: What are the method and effect of post-stack inversion in lithology prediction?

A: The response difference of each lithology on the logging curve is used to finely divide the positions where the coal seam, sandstone and mudstone of the selected well are developed. Through petrophysical analysis, the intersection analysis of wave impedance curve, natural gamma curve and lithology curve of each hole in the work area is made, and the intersection diagram of natural gamma curve and wave impedance curve of each well hole is obtained. It can be seen from the figure that the wave impedance parameters can distinguish sandstone and mudstone in each formation. The number of the sampling points more (or less) than the wave impedance threshold of this layer at each CDP point is counted, the result of the sampling points x sampling rate/2 is taken as the time thickness of this layer and multiplied by the velocity of rock layer to obtain the thickness of rock layer. The prediction effect is good.


Q2: What are the method and effect of pre-stack AVO inversion in gas-bearing property prediction?

A: By comparing logging data and using logging data with water saturation in the area, analyze the relationship between water saturation and reservoir density, acoustic time difference and Poisson's ratio, and obtain intercept and gradient attributes based on AVO. The AVO intercept P and gradient G attributes of the target stratum are extracted by using the pre-stack CRP gathers. Based on the analysis of AVO response characteristics of gas-bearing and non-gas-bearing wells, the pseudo Poisson's ratio (P+G) attributes are used as AVO fluid factor sensitive attributes to detect the gas-bearing property of the reservoir, and the pseudo Poisson's ratio attribute characteristics of wellhead position are extracted. It is believed that the favorable gas-bearing areas are characterized by low pseudo Poisson's ratio. It is proved by drilling verification that the location of the resource-rich area predicted by this feature is accurate.

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