In order to accurately predict the high-production areas in CBM reservoirs, we identified the main geological factors controlling the CHM production. Based on the statistical analysis data of the geological and production area and seismic prediction methods, the comparative influence of the five main geological factors was studied. The validity of the seismic prediction method was further evaluated. The results show that the production of a GEM well is influenced by the reservoir structure, gas content, permeability, and coal-body structure. The above four geological controlling factors can be accurately evaluated by the seismic attributes. The proposed high-production area seismic prediction method can be applied for accurate localization of the high-production areas. When the high-production evaluation index is lower than 0.2, the daily gas production exceeds 1000 The method can provide an effective instrument for evaluating formation productivity.
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1. INTRODUCTION
In recent years, the coalbed methane (CBM) industry in China has been developing rapidly. The CBM reservoirs are characterized by a relatively low average production of wells and significant difference in production between the wells; hence the benefits of the development are not always clear [1]. The fundamental reason is that the existing engineering technology is not adapted to the diversity of geological conditions of CBM reservoirs [2]. At present, the main method of improving the production is based on the accurate localization of the high-production zone. In conventional reservoirs the 3D seismic prediction technology is effectively used. It enables one to invert seismic parameters, evaluate their physical significance, and obtain a 3D display of the formation [3]; hence it can be effectively used to predict the high production zone. Many authors have carried out the research on formation evaluation methods of CBM reservoirs. The gas content is evaluated by 3D seismic survey, and the density and acoustic time are interpreted as the key factors for the gas content prediction [4]. The selected seismic attributes are combined using D-S evidence theory. and the results are used to predict the gas-enriched area [5]. Inverse correlations between methane content and elastic properties of the coal beds may exist in general in high- and medium-rank OM reservoirs, and this may lay the foundation for a theoretical basis of CBM AVO [6].
Three methods are commonly used to predict the expansion of natural fractures. For instance. Huo Lina adopted post-stack attributes, such as coherence, curvature, inclination, variance, etc., to predict the fractures [7]. Du Wenfeng adopted the above attributes to predict the fracture zone and pointed out that this method is mainly aimed at the prediction of small faults [8]. In the second method, the Poisson's ratio difference data obtained by the AVO technology were used for the detection of coal seam fractures. Gregory [9] found that fractures in rock cause an increase in the ratio of vertical and horizontal wave velocities and an increase in the Poisson's ratio. Ramos and Davis showed that the Poisson's ratio of coal seam samples was related to the fracture density [10]. The third method of detecting the coal seam fractures is based on the p-wave anisotropy theory. At the present time the coal body structure is usually identified by logging data, while the prediction of coal body structure by seismic methods needs further study [11]. In order to predict the high production areas of the OM reservoirs by seismic data, we identified the main geological factors that influence OM production.
The data statistics analysis was based on the geological and production data. The analyzed seismic data described the major geological factors, including the reservoir structure, thickness, gas content, fractures, and coal-body structure. The seismic method of high-production area prediction was developed and elastic modulus ranges from 0.6 to 2.5 GPa, with an average of 1.2 GPa. The direction of the maximum horizontal principal stress is northeast, and the stress value ranges between 13 and 42 MPa [13].
2. FACTORS CONTROLLING THE CBM HIGH-PRODS:MON ZONE
2.1 Faults and Collapse Columns
The development practices in the southern Qinshui Basin show that the faults and collapse columns have a negative effect on the gas storage in the 3# coal seam [14]. Faults and collapse columns may provide the escape channels for CBIst thus leading to a lower gas content. Hence the accurate localization of faults and collapse columns is essential for prediction of the high-production zone.
2.2 Gas content
Gas content is the material basis for the high production of CBM wells [15]. The stable single-well daily gas production increases with the increase of gas content. When the gas content is lower than 15 m3/t, the single well gas production is generally less than 800 mild, which is not sufficient for beneficial industrial development. This illustrates that gas content evaluation is essential for the prediction of the high-production zone.
2.3 Permeability
The original permeability has an important influence on the seepage of water and methane in the coal seam [16]. Daily production increases with increase in permeability. When the coal seam permeability is lower than 0.1 mD, the daily production is less than SOO m'. Hence, prediction of the permeability is essential for the prediction of the high-production zone. However, the permeability is difficult to evaluate directly by the seismic prediction methods. Instead, the method of evaluation of the natural fractures development is adopted, as the coal seam permeability shows a positive correlation with the development degree of fractures [17].
2.4 Coal-body structure
The coal-body structure significantly affects the length and complexity of the hydraulic fractures [18]. The structure of the bulk primary coal or cataclastic coal has a positive effect on hydraulic fractures, while that of the fine or mylonitic coal has a negative impact. The pilot hydraulic fracture monitoring and the well logging analysis illustrated that the higher proportion of tectonic coal correlated with the shorter hydraulic fractures [19]. Hence the evaluation of the coal body structure of the formation is important for the prediction of the daily gas production.
3. HIGH-PRODUCTION ZONE SEISMIC PREDICTION TECHNOLOGY
3.1 Multiple attributes seismic interpretation of structure
In order to reflect the microstructure of the coal seam, the automatic tracking interpretation method is adopted. based on accurate interpretation of the waveform and phase attributes. The coal seam 3' is characterized by strong reflection and good continuity of seismic signals.
The selected attribute profiles, such as instantaneous frequency, instantaneous phase, and reflection strength, are adopted to interpret the faults, which can improve the reliability of the seismic interpretation [20]. The coherence attribute and curvature attribute are also adopted to identify the strike and the size of the faults, as well as to characterize the small faults. Practice shows that the above method can accurately identify the faults with a slip larger than 10 m. The interpretation of collapse column is mainly based on its reflection characteristics of the seismic profile. Meanwhile, the coherence body and slice analysis along the target formation is used for better authentication. The minimum recognized diameter is 50 m.
The study area is a typical mountainous terrain. The buried depth and lateral lithology of the coal seam vary greatly. Therefore, time-depth conversion by fitting velocity easily causes distortion of structural morphology. The superimposed velocity spectrum helps to obtain values close to the actual formation velocity. Therefore. the superimposed velocity spectrum method is selected to evaluate the accurate velocity field and to improve the accuracy of the structure map.
3.2 Logging-constrained wave impedance inversion determining the thickness
Analysis of the well-logging data shows that the longitudinal wave impedance of the coal seam is obviously lower than that of sand mudstone or carbonate rock, so acoustic impedance inversion can be used to predict the thickness of the coal seam. As the coalbed gas reseivoir is relatively thin, the accuracy and resolution of the ordinary seismic data inversion and the limitation of the seismic bandwidth cannot meet the development requirements. Taking advantage of the abundant well logging data, the model inversion method with high longitudinal resolution is adopted to predict the thickness of the coal seam. The high-frequency and low-frequency logging data help to improve the seismic bandwidth and to achieve the high resolution wave impedance data. As shown in Fig.l. the coal seam thickness determined by logging-constrained wave impedance inversion matches the thickness obtained by the well logging analysis, so the logging-constrained wave impedance inversion method is applicable to the high-rank coal seams.
3.3 Post-stack frequency attenuation attributes for gas content prediction
The seismic waves passing through the gas bearing strata will result in energy attenuation, manifested in the loss of the high-frequency energy [21]. The seismic attenuation can be qualified by the change in the frequency spectrum. The spectrum analysis helps to evaluate the sensitivity of the spectral parameters on the coal seam gas content, including such features as spectral imaging, total energy, maximum energy, low frequency, full frequency, energy ratio, attenuation gradient, and attenuation frequency. The results show that the frequency attenuation gradient is highly sensitive to the gas content of the coal seam. As shown in Fig. 2, the gas content increases with decrease in frequency attenuation gradient attributes, with a coincidence rate of about 95%, which indicates that the frequency attenuation gradient attributes can be successfully used for the CBM gas content prediction.
3.4 Pre-stack azimuth angle anisotropy attributes predicting the fractures
The development degree of fractures is the dominant factor for the coal seam permeability. The pre-stack azimuth angle anisotropy attributes can identify the fractures ranging from several centimeters to meters [22]. The fractures cause anisotropy in the seismic attributes, and the fitted anisotropy ellipse can be used to predict the development degree of fractures. The pre-stack seismic data have an advantage compared with the post-stack seismic data: they contain abundant seismic reflection information. such as azimuth angle and incidence angle, and can be used to improve the prediction of microfractures or cleats.
The wide azimuth acquisition method is used for three-dimensional seismic data gathering. The data were registered for five azimuth angles 18°, 54°, 90°, 126°, and 162°. The attribute anisotropy analysis for the selected points on the line of the coal seam 3' is used to predict the cleats from the above five azimuth angles. Figure 3 shows the relationship between the pre-stack anisotropy attributes of azimuth angles and the major fracture density for the coal samples from the test wells. The major density of fractures is identified by scanning electron microscopy. The results show that the major density of fractures increases with increase in pre-stack anisotropy attributes of azimuth angles, with a coincidence rate of about 82%, which complies with the fracture prediction requirements in engineering.
3.5 Dual lateral resistivity logging-constrained acoustic inversion for coal-body structure prediction
With decrease in size of the coal rock particles, the acoustic transit time log increases while the resistivity decreases [23]. As shown in Fig. 4a, the increase in the proportion of fragmented and mylonitic coal in the overall coal seam structure leads to the increase in the acoustic transit time, which is consistent with the previous research results. The acoustic transit time can be adopted for characterizing the predicted fracture development trend. However, the dependence between electrical resistivity and the coal body structure is relatively poor. As shown in Fig. 4b. the proportion of fragmented and mylonitic coal increases with increase in the difference between the deep and short lateral resistivity signals, with a coincidence rate of about 80%, which is higher than that of acoustic transit time logging. Hence. the dual lateral resistivity logging-constraint acoustic inversion method is adopted to predict the development of the fractures.
4. HIGH-PRODUCIIONAREA SEISMIC PREDICTION METHOD
In order to create a comprehensive high-production evaluation method, the daily gas production is taken as the primary parameter. The following four types of seismic attributes are taken as secondary parameters: logging-constrained wave impedance inversion (U1), post-stack frequency attenuation attributes (U2), pre-stack azimuth angle anisotropy attributes (U), and dual lateral resistivity logging-constrained acoustic inversion (U4). The weight of each parameter is determined based on the gray correlation analysis method. The weighting coefficients for Ul , U2, U, and U, are 0.18, 0.26, 0.35, and 0.22, respectively. The high-production evaluation index is calculated by the following equation:
where UI is the high-production evaluation index, U1 is the logging-constrained wave impedance inversion, U2 is the post-stack frequency attenuation attributes, U3 is the pre-stack azimuth angle anisotropy attributes, and U, is the dual lateral resistivity logging-constrained acoustic inversion.
The relationship between the daily gas production and the high-production evaluation index is shown in Figure 5. The results show that the daily gas production decreases with increase in the high-production evaluation index, with a high coincidence rate. The results indicate that the high-production evaluation method can be used for accurate prediction of the production and localization of the high-production zone. Figure 5 shows that, with the high-production evaluation index under 0.2, the daily gas production exceeds 1000 m3, which correlates with the high production area.
5. CONCLUSIONS
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1.
The production of the CBM well is influenced by four key geological factors, such as reservoir structure, gas content, permeability, and coal-body structure. The above geological factors can be accurately predicted by seismic attributes analysis.
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2.
The multiple attributes seismic interpretation method can be used for the structure interpretation. The logging-constrained wave impedance inversion is applicable for the prediction of the coal seam thickness. The gas content of the coal seam can be predicted by frequency attenuation gradient, and the gas content increases with decrease in frequency attenuation gradient attributes. The major density of natural fractures increases with increase in pre-stack anisotropy attributes of azimuth angles, so the natural fractures can be predicted by pre-stack anisotropy attributes of azimuth angles. The coal body structure can be predicted by the dual lateral resistivity logging constraint acoustic inversion method.
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3.
The proposed high-production area seismic prediction method can be used for the accurate prediction of the high-production area. With the high-production evaluation index under 0.2, the daily gas production exceeds 1000 m3. Hence an index under 0.2 indicates a high-production area.
Change history
19 March 2020
To the article ���Research and Application of High-Production Area Seismic Prediction Technology for High-Rank Coalbed Methane Reservoir,��� by Liu Yumin, Li Xuesong, Sun Yonghe, Li Minghui, Du Jingguo, Vol. 55, No. 5, pp. 606-614, November, 2019
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Acknowledgement
This study was financially supported by the National Natural Science Foundation of China (Grant No. 41572127).
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Translated from Khimiya i Tekhnologiya ropily i Mare!, No. 5, pp. 66— 70, September — October, 2019.
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Turnip, L., Xuesone, L., Yonghe, S. et al. Research and Application of High-Production Area Seismic Prediction Technology for High-Rank Coalbed Methane Reservoir. Chem Technol Fuels Oils 55, 606–614 (2019). https://doi.org/10.1007/s10553-019-01073-x
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DOI: https://doi.org/10.1007/s10553-019-01073-x