Model and method for predicting gas development potential of rock bed based on three-dimensional seismic data

Abstract

The present application relates to the technical field of geological evaluation and exploration of gas reservoirs using three-dimensional seismic data, and particularly relates to a model and method for predicting the development potential of rock strata based on three-dimensional seismic data, which predicts the development potential of rock strata based on three-dimensional seismic data, obtains fault throw and fault zone width by interpreting three-dimensional seismic data, obtains strike-slip fault deformation intensity S after normalizing the data, and predicts the development potential of rock strata according to the size of the strike-slip fault deformation intensity S, so as to realize the quantitative correlation between strike-slip fault structural features and natural gas production, and to convert the fault control on reservoirs from empirical judgment to quantifiable evaluation criteria, and to provide a reference for the research on fault control on reservoirs in complex structural zones.

Description

Technical Field

[0001] This invention relates to the technical field of gas reservoir geological evaluation and exploration using seismic 3D data, and particularly to a model and method for predicting the development potential of natural gas in rock formations based on seismic 3D data. Background Technology

[0002] In existing technologies, to comprehensively evaluate the control effect of strike-slip fault displacement and fault zone width on natural gas enrichment, a weighted summation method is usually used for quantitative evaluation. However, the setting of weighting coefficients is somewhat subjective. Furthermore, to analyze the intensity of fault activity, trend surface techniques are generally used to fit formation deformation, with positive and negative values ​​representing formation arching or subsidence. These existing methods are difficult to accurately and quantitatively characterize the multi-phase activity and horizontal displacement intensity of strike-slip faults and are easily affected by subsequent alteration. Summary of the Invention

[0003] To address the technical problems existing in the prior art, this invention provides a model for predicting the development potential of natural gas in rock strata based on three-dimensional seismic data. Specifically, the model is as follows:

[0004]

[0005] Where S is the strike-slip fracture deformation strength; D is the fracture displacement in ms; W is the fracture zone width in m; n is the number of fracture displacements, i is 1, 2, 3, ...;

[0006] When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment.

[0007] When 0.6≤S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation;

[0008] When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

[0009] Based on the above scheme, the fault displacement D and the fault zone width W are obtained by measuring the profile at intervals of 10 traces after interpreting the three-dimensional seismic data using Petrel software.

[0010] This invention also provides a method for predicting the development potential of natural gas in rock formations based on three-dimensional seismic data, the method comprising the following steps:

[0011] S1: Interpret the fractures in the 3D seismic data, extract the profile fault displacement D and fracture zone width W data, and obtain the fault displacement data and fracture zone width data of the strike-slip fracture.

[0012] S2: Normalize the fault displacement data and fault zone width data to obtain the normalized fault displacement. and the normalized fracture zone width ;

[0013] S3: Based on the normalized fault displacement data and fracture zone width data, the strike-slip fracture deformation strength S is established, as shown in the following formula:

[0014]

[0015] Where D is the fault displacement in milliseconds (ms); W is the width of the fault zone in meters (m). The normalized fault distance. The normalized width of the fracture zone;

[0016] S4: Predict the natural gas development potential of the target rock formation based on the magnitude of the strike-slip fracture deformation intensity S.

[0017] Based on the above scheme, the method for predicting the natural gas development potential of the target strata in step S4 according to the magnitude of the strike-slip fracture deformation intensity S is as follows:

[0018] When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment.

[0019] When 0.6≤S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation;

[0020] When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

[0021] Based on the above scheme, step S1: interpret the seismic data fractures, extract the profile fault displacement and fault zone width data, and obtain the fault displacement data and fault zone width data of strike-slip faults, specifically including:

[0022] After interpreting the three-dimensional seismic data of the target area using Petrel software, the fault displacement and fault zone width data of the profile were extracted using a 10-channel interval system.

[0023] Based on the above scheme, step S2: the step of normalizing the fault displacement data and fault zone width data, specifically includes:

[0024] S21: The dislocation value obtained in step S1 , , ... The normalization process is performed using the following formula:

[0025]

[0026] Where D is the dislocation distance, the unit of dislocation distance is ms, n is the number of dislocation distances, and i is 1, 2, 3, ...;

[0027] S22: The fracture zone width value obtained in step S1 , , ... Normalization is performed using the following formula:

[0028]

[0029] Where W is the width of the fault zone, in meters; i is 1, 2, 3, ...

[0030] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0031] This invention's model predicts the natural gas development potential of rock formations based on three-dimensional seismic data. By interpreting the three-dimensional seismic data, fault displacement and fault zone width are obtained. After data normalization, the strike-slip fault deformation intensity S is obtained. Based on the magnitude of the strike-slip fault deformation intensity S, the natural gas development potential of the rock formations is predicted, thus realizing a quantitative correlation between strike-slip fault structural characteristics and natural gas production. This transforms the fault-controlled reservoir effect from empirical judgment to a quantifiable evaluation standard, and also provides a reference for the study of fault-controlled reservoirs in complex structural zones. Using the prediction method of this invention, high-yield potential areas can be accurately identified from target area classification maps, achieving a leap from qualitative experience to quantitative prediction in the selection of natural gas exploration targets. This invention completes the quantitative characterization of the strike-slip fault-controlled reservoir effect, which is helpful for the exploration and development of deep carbonate gas reservoirs.

[0032] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0033] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0034] Figure 1 This is a schematic diagram of the plane and corresponding cross-section of the selected study area fracture F6 according to an exemplary embodiment, wherein (a) is a plan view of the selected study area fracture F6 and (b) is a schematic cross-section of the selected study area fracture F6.

[0035] Figure 2 This is a schematic diagram illustrating a method for measuring break distance according to an exemplary embodiment;

[0036] Figure 3 This is a schematic diagram illustrating a method for measuring the width of a fracture zone according to an exemplary embodiment;

[0037] Figure 4 This is a diagram illustrating the correlation between multi-parameter coupling and average annual natural gas production in the study area, based on an exemplary embodiment. Detailed Implementation

[0038] The following description and accompanying drawings fully illustrate specific embodiments of this application to enable those skilled in the art to practice them. Some parts and features of some embodiments may be included in or replace parts and features of other embodiments.

[0039] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0040] Example 1

[0041] This invention provides a model for predicting the development potential of natural gas in rock strata based on three-dimensional seismic data. Specifically, the model is as follows:

[0042]

[0043] Where S is the strike-slip fracture deformation strength; D is the fracture displacement in ms; W is the fracture zone width in m; n is the number of fracture displacements; i is 1, 2, 3, ...;

[0044] When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment.

[0045] When 0.6≤S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation;

[0046] When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

[0047] Specifically, the fault displacement D and fault zone width W are obtained by interpreting the three-dimensional seismic data (SEGY format) using Petrel software and measuring them at intervals of 10 traces on the profile.

[0048] Example 2

[0049] Based on the model in Example 1, the present invention also provides a method for predicting the development potential of natural gas in rock formations based on three-dimensional seismic data, the method comprising the following steps:

[0050] S1: Interpret the fractures in the 3D seismic data, extract the profile fault displacement D and fracture zone width W data, and obtain the fault displacement data and fracture zone width data of the strike-slip fracture.

[0051] Specifically, Petrel was used to interpret the fractures in the 3D seismic data. The fault displacement and fracture zone width data of the profile were extracted using a 10-interval system to obtain the fault displacement information of the strike-slip fracture and clarify the fracture zone width value.

[0052] The above scheme extracts parameters based on high-density seismic profile interpretation (10-channel interval), and combines them with a coupled model to quantitatively characterize the intensity of multi-stage activity and horizontal displacement of strike-slip faults, overcoming the limitations of later-stage modification interference of trend surface technology; relying on the Petrel platform, it realizes automated parameter extraction and calculation, significantly improving the evaluation efficiency of single faults compared with traditional methods, and providing a universal technical standard for all lithologies, including complex tectonic zones such as deep carbonate rocks.

[0053] S2: Normalize the fault displacement data and fault zone width data to obtain the normalized fault displacement. and the normalized fracture zone width ;

[0054] S21: The dislocation value obtained in step S1 , , ... The normalization process is performed using the following formula:

[0055]

[0056] Where D is the dislocation distance, the unit of dislocation distance is ms, n is the number of dislocation distances, and i is 1, 2, 3, ...;

[0057] S22: The fracture zone width value obtained in step S1 , , ... Normalization is performed using the following formula:

[0058]

[0059] Where W is the width of the fault zone, in meters; i is 1, 2, 3, ...

[0060] S3: Based on the normalized fault displacement data and fracture zone width data, the strike-slip fracture deformation strength S is established, as shown in the following formula:

[0061]

[0062] Where D is the fault displacement in milliseconds (ms); W is the width of the fault zone in meters (m). The normalized fault distance. The normalized width of the fracture zone;

[0063] S4: Predict the natural gas development potential of the target rock formation based on the magnitude of the strike-slip fracture deformation intensity S.

[0064] Based on the above scheme, the method for predicting the natural gas development potential of the target strata in step S4 according to the magnitude of the strike-slip fracture deformation intensity S is as follows:

[0065] When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment.

[0066] When 0.6≤S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation;

[0067] When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

[0068] The above scheme avoids the defects of manually setting weight coefficients in traditional methods by normalizing the coupling calculation of the fault displacement D and the fracture zone width W, and realizes an objective and quantitative evaluation of the deformation strength of strike-slip fracture.

[0069] The core of the model and method of this invention lies in the fact that all of the entire dataset... The arithmetic mean of is equal to one, and similarly... =1. The S value is two random variables with a mean of 1. and The product of S and S. According to the principle of probability distribution, S < 1 means that at least one of the two parameters at this point is below the average level. S < 0.6 is a critical point that significantly deviates from the average value of 1 (the setting of 0.6 is based on the physical threshold of the limited conductivity of the fracture). Geomechanical studies show that fractures need to reach a certain deformation strength to form a connected fracture network, overcome capillary resistance, and become effective fluid conduction channels. When the S value is below 0.6, it indicates that the fault displacement and the width of the fracture zone are both small, the fracture zone is in a "closed" state, and its permeability does not meet the lower limit requirements for effective migration and accumulation of oil and gas; therefore, S < 0.6 is defined as a low-potential zone.

[0070] An S value much greater than 1 is a low-probability event, which requires two normalization parameters. and Both must be significantly greater than 1 and much higher than the arithmetic mean; when both normalized parameters are much higher than the arithmetic mean, this invention defines "significantly higher than the mean" as a multiple of the "mean":

[0071] Suppose that the discontinuity and width of a point are both K times the average value of the study area (K>1), that is: S=K 2S0 represents the original deformation strength value. Geological studies indicate that when the strength of a structural parameter reaches 1.4 times the regional average, it is usually considered a significant anomaly. When K=1.4, K... 2 =1.96 is approximately equal to 2.0. Therefore, using S>2.0 as the threshold, we can statistically identify special points where both the fault displacement and width far exceed the average value. These points correspond precisely to the core area of ​​the fault with multiple phases of intense activity.

[0072] This application will quantitatively calculate the deformation intensity of strike-slip faults, realize the quantitative correlation between the structural characteristics of strike-slip faults and natural gas production, and transform the fault-controlled reservoir effect from empirical judgment to a quantifiable evaluation standard.

[0073] Example 3

[0074] Based on the model of Example 1 and the method of Example 2, this invention provides a specific prediction method using fracture F6 in a certain study area as an example, and verifies the prediction results.

[0075] 1. Distance Statistics

[0076] like Figure 1 As shown, Petrel software is used to interpret faults in seismic data. Figure 2 As shown, the dislocation distance is accurately measured at 10 intervals on the cross section. The system acquires and records the dislocation distance data, and some data are shown in Table 1.

[0077] Table 1. Statistics of Displacement

[0078]

[0079] 2. Displacement normalization treatment

[0080] The fault displacement data obtained in step 1 is normalized. Taking D1 as an example, this value is the fault displacement of fracture F6 at Inline 3585, calculated according to the formula... Calculate the normalized result, and then repeat this process to obtain the normalized fault displacement value for each measuring point along the entire fault.

[0081] Table 2 Normalized Displacement Data

[0082]

[0083] 3. Statistics on the width of the fault zone

[0084] Use the same measurement method as in step 1, such as Figure 3 As shown, the Petrel software was used to systematically extract the fault zone width from the seismic profile (measurement interval was 10 traces), and the fault zone width data were obtained and recorded. Some data are shown in Table 3.

[0085] Table 3. Statistics on the width of the fracture zone

[0086]

[0087] 4. Normalization of fault zone width

[0088] The fracture zone width data obtained in step 3 is normalized. Taking W1 as an example, this value is the fracture zone width of fracture F6 at Inline 3585, calculated according to the formula... Calculate the normalized result and obtain the normalized width value for each measuring point in sequence. .

[0089] Table 4. Normalized Fault Zone Width Data

[0090]

[0091] 5. Calculation of deformation strength at strike-slip fracture

[0092] Based on the normalized fracture distance obtained in steps 2 and 4 and normalized fault zone width The strike-slip fracture deformation strength S is calculated using the following formula:

[0093]

[0094] Where D is the fault displacement in milliseconds (ms); W is the width of the fault zone in meters (m). and The normalized break distance and width are given by i, where i is 1, 2, 3, ...

[0095] Table 5. Strike-slip fracture deformation strength data

[0096]

[0097] 6. Establish a grading and evaluation standard for the potential of strike-slip faults to control reservoirs based on S-values;

[0098] When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment.

[0099] When 0.6≤S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation;

[0100] When S≥2.0, it is defined as a high-potential zone, with strong fault activity and well-developed fractured-vuggy reservoirs, which is a "sweet spot" for high-yield enrichment of natural gas.

[0101] The correlation between deformation strength and natural gas production was verified as follows:

[0102] The deformation intensity S-value of the strike-slip fault obtained in step 5 was correlated with the measured annual average natural gas production data of the study area. Specifically, the correlation between fault displacement and fault width alone and natural gas production was poor, with discrete points showing high fault displacement and low production, low fault displacement and high production, and high width and high production. This proves that single data cannot reliably characterize the comprehensive gas-bearing capacity of faults because it fails to couple the two key geological factors of fault width and fault displacement. Figure 4 As shown, when S < 0.6, such as in W1 and W2, the average annual production is extremely low, representing ineffective fracture zones. W7 and W8 show similar fault displacements D, but due to differences in their fracture zone widths W, the S values ​​differ, resulting in a several-fold difference in final production. By comparing the fracture zone width and displacement with the phasing intensity values ​​laterally, direct and effective decision-making basis is provided for oil and gas exploration. The results indicate that, as... Figure 4 As shown, the deformation strength S is significantly positively correlated with natural gas production.

[0103] The standard was applied to analyze fault F6 in this embodiment, and the results are shown in Table 5. The distribution of S values ​​shows that the vast majority of measuring points (66.67%) fall within the medium-potential zone, representing a common characteristic of fault zones. The high-potential zone accounts for the smallest proportion (10%), which precisely aligns with the geological consensus that "high-potential sweet spots for oil and gas production are always scarce."

[0104] The data clearly indicates three top-priority drilling targets: Inline 3695 (S=2.55), 3795 (S=1.86), and 3835 (S=1.73). Point 3695, being the highest value along the entire line, is the center of fault zone activity and should be the target point for the highest-priority well placement. Inline 3765 (S=0.32) and 3775 (S=0.24), both less than 0.6, are clearly identified as inefficient fault zones, avoiding exploration risks that might arise from traditional experience-based judgments.

[0105] This invention eliminates the subjectivity of evaluation: by normalizing and coupling the displacement D and the fault zone width W, it avoids the defects of manually set weight coefficients in traditional methods, thus achieving an objective and quantitative evaluation of strike-slip fault deformation intensity; based on high-density seismic profile interpretation (10-channel interval), parameters are extracted and combined with the coupling model to quantitatively characterize the intensity of multi-stage activity and horizontal displacement of strike-slip faults, overcoming the limitations of later-stage modification interference in trend surface technology; it clarifies that the deformation intensity S of strike-slip faults is significantly correlated with natural gas production, improving the accuracy of identifying high-yield potential areas in target regions and promoting the leap from empirical judgment to quantitative prediction in fault-controlled reservoir evaluation; at the same time, relying on the Petrel platform, it realizes automated parameter extraction and calculation, significantly improving the evaluation efficiency of single faults compared with traditional methods, applicable to all lithologies, and providing a universal technical standard for complex tectonic areas such as deep carbonate rocks.

[0106] Finally, it should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0107] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A model for predicting the development potential of natural gas in rock strata based on three-dimensional seismic data, characterized in that, The model is as follows: Where S is the strike-slip fracture deformation strength; D is the fracture displacement in ms; W is the fracture zone width in m; n is the number of fracture displacements; i is 1, 2, 3, ...; When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment. When 0.6 ≤ S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation; When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

2. The model for predicting the development potential of natural gas strata based on three-dimensional seismic data according to claim 1, characterized in that, The fault displacement D and fault zone width W were obtained by measuring the data on the profile at intervals of 10 traces after interpreting the three-dimensional seismic data using Petrel software.

3. A method for predicting the development potential of natural gas in rock strata based on three-dimensional seismic data, characterized in that, Use the model as described in claim 1 or 2.

4. The method for predicting the development potential of natural gas strata based on three-dimensional seismic data according to claim 3, characterized in that, Includes the following steps: S1: Interpret the fractures in the 3D seismic data, extract the profile fault displacement D and fracture zone width W data, and obtain the fault displacement data and fracture zone width data of the strike-slip fracture. S2: Normalize the fault displacement data and fault zone width data to obtain the normalized fault displacement. and the normalized fracture zone width ; S3: Based on the normalized fault displacement data and fracture zone width data, the strike-slip fracture deformation strength S is established, as shown in the following formula: Where D is the fault displacement in milliseconds (ms); W is the width of the fault zone in meters (m). The normalized fault distance. The normalized width of the fracture zone; S4: Predict the natural gas development potential of the target rock formation based on the magnitude of the strike-slip fracture deformation intensity S.

5. The method for predicting the development potential of natural gas strata based on three-dimensional seismic data according to claim 4, characterized in that, The method for predicting the natural gas development potential of the target strata based on the magnitude of the strike-slip fracture deformation intensity S in step S4 is as follows: When S < 0.6, it is defined as a low-potential zone, with weak fault modification and poor natural gas enrichment. When 0.6 ≤ S<2.0, it is defined as a medium potential zone, where the fault control effect is obvious, and it is a favorable zone for hydrocarbon accumulation; When S≥2.0, it is defined as a high-potential zone, with strong fault activity, well-developed fractured-vuggy reservoirs, and is a high-yield and rich natural gas zone.

6. The method for predicting the development potential of natural gas strata based on three-dimensional seismic data according to claim 4, characterized in that, Step S1: Interpret the seismic data fractures, extract the profile fault displacement and fault zone width data, and obtain the fault displacement data and fault zone width data of strike-slip faults, specifically including: After interpreting the three-dimensional seismic data of the target area using Petrel software, the fault displacement and fault zone width data of the profile were extracted using a 10-channel interval system.

7. The method for predicting the development potential of natural gas strata based on three-dimensional seismic data according to claim 4, characterized in that, Step S2: The step of normalizing the fault displacement data and fault zone width data, specifically including: S21: The dislocation value obtained in step S1 , , ... The normalization process is performed using the following formula: Where D is the dislocation distance, the unit of dislocation distance is ms, n is the number of dislocation distances, and i is 1, 2, 3, ...; S22: The fracture zone width value obtained in step S1 , , ... Normalization is performed using the following formula: Where W is the width of the fault zone, in meters; i is 1, 2, 3, ...

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