A Prediction Method for SAC Fluid Interface in Deep-Water, Low-Well Lithologic Reservoirs

Abstract

This invention provides a method for predicting the SAC fluid interface in lithologic oil and gas reservoirs in deep water areas with few wells. The prediction method includes the following steps: (1) establishing a database of fluid interfaces and drilling success rates based on the actual drilling fluid interface data of the study area or globally; (2) determining the key factors affecting the fluid interface based on the database obtained in step (1), combined with regional oil and gas reservoir characteristic analysis and statistical data and exploration experience in the study area; (3) analyzing and evaluating the categories and respective influence degrees of the key factors obtained in step (2), establishing SAC scoring standards to guide the prediction of the fluid interface. The prediction method provided by this invention fully utilizes seismic information, solves the problem of fluid interface confirmation in the absence of actual drilling, and significantly reduces the difficulty of fluid interface prediction.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas reservoir exploration technology, and relates to a method for predicting fluid interfaces in oil and gas reservoirs, particularly a method for predicting SAC fluid interfaces in lithologic oil and gas reservoirs in deep water areas with few wells. Background Technology

[0002] Predicting fluid interfaces in oil and gas reservoirs often relies on well drilling or regression analysis of oil, gas, and water pressures within the specific oil and gas field. When no wells reveal the fluid interface or when no water layer is encountered (e.g., at the oil or gas bottom), technicians primarily use pre-stack inversion, fluid factors, or flat-point reflections for qualitative prediction. However, in practical applications, these methods still have several shortcomings: pre-stack inversion is affected by the number and distribution of wells and sensitivity parameters, leading to uncertainty in its effectiveness; fluid factors are generally obtained indirectly through parameters such as P-wave and cross-slope impedance, which are prone to cumulative errors, often failing to meet expectations; and in the absence of a clear tectonic background and with thin reservoir sand bodies, the fluid interface indication effect of flat-point reflections cannot be applied to the evaluation of lithological trap oil and gas reservoirs. These deficiencies limit the use of existing technologies for fluid interface identification.

[0003] Currently, with the continuous improvement of seismic technology, pre-stack seismic data are being used more and more. The large amount of information contained in these data is directly used in reservoir characterization and hydrocarbon detection, mainly for qualitative hydrocarbon identification, but has not yet been used for fluid interface prediction.

[0004] Therefore, how to provide a method for predicting fluid interfaces in oil and gas reservoirs, fully utilize seismic information, solve the problem of fluid interface identification without actual drilling, and significantly reduce the difficulty of fluid interface prediction has become an urgent problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the SAC fluid interface in lithologic oil and gas reservoirs in deep water areas with few wells. This method fully utilizes seismic information, solves the problem of fluid interface determination in the absence of actual drilling, and significantly reduces the difficulty of fluid interface prediction.

[0006] To achieve this objective, the present invention employs the following technical solution:

[0007] This invention provides a method for predicting the SAC fluid interface in lithologic oil and gas reservoirs in deep-water, low-well areas. The prediction method includes the following steps:

[0008] (1) Establish a database of fluid interface and drilling success rate based on the actual drilling fluid interface conditions in the study area or globally;

[0009] (2) Based on the database obtained in step (1), and by combining the regional oil and gas reservoir characteristics analysis and statistics with the exploration experience of the study area, the key factors affecting the fluid interface are determined.

[0010] (3) Analyze and evaluate the categories of key factors obtained in step (2) and their respective degrees of influence, and establish the SAC scoring standard to guide the prediction of fluid interfaces.

[0011] This invention provides a set of deep-water sedimentary systems based on SAC fluid interface identification technology. By establishing quantitative evaluation standards for key parameters that are indicative of the oil-gas-water interface, and integrating regional oil and gas reservoir characteristics and expert experience for comprehensive evaluation and scoring, it achieves accurate prediction of oil and gas reservoir fluid interfaces, fully exploits seismic information, solves the problem of fluid interface identification in the absence of actual drilling, and significantly reduces the difficulty of fluid interface prediction.

[0012] In this invention, SAC refers to the conformance between the structural contour lines and the amplitude lines of seismic properties.

[0013] Seismic forward modeling shows that, under conditions of relatively stable underground reservoir properties, oil, gas, and water layers exhibit significant amplitude variations, with oil and gas layers showing stronger amplitudes than water layers. This indicates that amplitude has a clear indicative significance for fluid dynamics under certain geological conditions. Through seismic analysis combined with geophysical analysis, this oil-water / gas-water difference and its impact can be quantified to a certain extent. This application analyzes the SAC (Seismic Aquifer Convergence) influencing factors and establishes a scoring standard. Based on this, a set of standards is created for SAC evaluation, ultimately determining the fluid interface.

[0014] Preferably, the key factors mentioned in step (2) include the reliability of seismic data, the quality of amplitude attributes, the sensitivity of fluid response, the possible fluid interface, the consistency of tectonic amplitude, the consistency of top and bottom attributes and the degree of agreement with regional geological understanding.

[0015] Preferably, the evaluation of the reliability of the seismic data includes: conducting forward modeling using parameters obtained from the wellbore, comparing the actual amplitude values ​​of the seismic well bypass with the forward modeled amplitude values ​​of the wellbore parameters, analyzing the amplitude preservation of the seismic data, and determining the applicability of the seismic amplitude; and extracting amplitude curves at various angles for different target layers, and establishing a method for calculating the amplitude variation rate.

[0016] Preferably, the evaluation of the amplitude attribute quality includes: evaluating the difference in seismic response between the oil and gas reservoir / trap sand body and the surrounding rock, and the amplitude continuity within the oil and gas reservoir / trap, and calculating the average score of these two factors as the evaluation score of the amplitude attribute quality.

[0017] Preferably, the evaluation of fluid response sensitivity includes: based on the physical analysis of drilled rocks in the target area, calculating the seismic response through differences in physical property parameters, and determining the amplitude curves of the response of oil / gas layers and water layers.

[0018] Preferably, the prediction of possible fluid interfaces includes: analyzing the possible fluid interface locations at amplitude variations within the study area, and predicting the fluid interface depth by combining geological knowledge of the oil and gas reservoir with drilling results.

[0019] Preferably, the analysis of structural amplitude consistency includes: analyzing the degree of agreement between the preferred seismic attribute change line and the structural contour line, selecting the structural contour line that is closer to the attribute change line and has a better superposition trend as the predicted fluid interface value, comparing it with the regional assessment standard, and guiding the identification of the fluid interface location.

[0020] Preferably, the evaluation of the consistency of top and bottom attributes includes: picking up and comparing the fluid interface depths determined after analyzing the consistency between the top and bottom attribute change lines and the structural contour lines, and performing fault tolerance analysis.

[0021] Preferably, the evaluation of the degree of agreement of regional geological understanding includes: evaluating each geological influencing factor based on regional geological analysis and sedimentary analysis, and finally determining the score of geological agreement by calculating the arithmetic mean.

[0022] Preferably, the evaluation of the degree of influence in step (3) includes: calculating the weight of each key factor and quantifying it into a score value.

[0023] Preferably, the weight assignment method is modified according to the actual geological conditions and the depth of exploration in the study area.

[0024] Preferably, the calculation formula involved in the SAC scoring standard is as follows:

[0025]

[0026] In the formula, A i The scores for each key factor; Q i , where n is the weighting factor for each key factor; n is 6.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] This invention provides a set of deep-water sedimentary systems based on SAC fluid interface identification technology. By establishing quantitative evaluation standards for key parameters that are indicative of the oil-gas-water interface, and integrating regional oil and gas reservoir characteristics and expert experience for comprehensive evaluation and scoring, it achieves accurate prediction of oil and gas reservoir fluid interfaces, fully exploits seismic information, solves the problem of fluid interface identification in the absence of actual drilling, and significantly reduces the difficulty of fluid interface prediction. Attached Figure Description

[0029] Figure 1 This is a flowchart of the prediction method provided by the present invention;

[0030] Figure 2 This invention provides a standard for evaluating the difference in seismic response between oil and gas reservoirs / trap sand bodies and surrounding rocks in the prediction method.

[0031] Figure 3 This is the evaluation standard for amplitude continuity within a closed loop in the prediction method provided by this invention;

[0032] Figure 4 This invention provides a prediction method that constructs an amplitude consistency evaluation standard.

[0033] Figure 5 This is a schematic diagram of the relationship between the oil-water interface and the top and bottom surfaces in the prediction method provided by this invention;

[0034] Figure 6 This invention provides a prediction method that uses a regional database to statistically analyze key factors and drilling success rates.

[0035] Figure 7 This is a weight factor analysis diagram in the prediction method provided by the present invention;

[0036] Figure 8 A comparison diagram of the difference between the actual earthquake amplitude and the well-side forward modeling amplitude in the prediction method provided in Example 1;

[0037] Figure 9 The seismic attribute map of a certain oilfield in the target area provided in Example 1;

[0038] Figure 10 This is an overlay map of seismic attributes and structural contour lines of an oilfield in the target area, provided in Example 1.

[0039] Figure 11 This is an overlay map of the top and bottom surface attributes and structural contour lines of the target sand body in the prediction method provided in Example 1.

[0040] Figure 12 Spider diagram of target weight factor Q in the prediction method provided in Example 1. Detailed Implementation

[0041] The technical solution of the present invention will be further illustrated below through specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the present invention and should not be construed as limiting the invention in any way.

[0042] This invention provides a method for predicting the SAC fluid interface in deep-water, low-well lithologic oil and gas reservoirs, such as... Figure 1 As shown, the prediction method includes the following steps:

[0043] (1) Establish a database of fluid interface and drilling success rate based on the actual drilling fluid interface conditions in the study area or globally;

[0044] (2) Based on the database obtained in step (1), and by combining the regional oil and gas reservoir characteristics analysis and statistics with the exploration experience of the study area, the key factors affecting the fluid interface are determined.

[0045] (3) Analyze and evaluate the categories of key factors obtained in step (2) and their respective degrees of influence, and establish the SAC scoring standard to guide the prediction of fluid interfaces.

[0046] Among them, the key factors mentioned in step (2) include the reliability of seismic data, the quality of amplitude attributes, the sensitivity of fluid response, the possible fluid interface, the consistency of tectonic amplitude, the consistency of top and bottom attributes and the degree of agreement with regional geological understanding.

[0047] Specifically, the analysis and evaluation methods for the above key factors are as follows:

[0048] ① A1: Data Quality Assessment

[0049] Based on the seismic data and actual drilling conditions in the study area, the reliability of using seismic data amplitude was determined; the accuracy of drilling data in the study area was verified by analysis; and the elastic parameter V obtained from the well was analyzed. p V s Forward modeling was conducted using parameters such as ρ, and the actual seismic amplitude in the seismic well bypass was compared with the forward modeled amplitude values ​​of the well parameters to analyze the amplitude preservation of the seismic data and determine the applicability of the seismic amplitude. For different target layers, amplitude curves at various angles were extracted, and a method for calculating the amplitude change rate was established.

[0050] The formula for calculating the amplitude change rate is as follows:

[0051]

[0052] In the formula, X i These are the forward-modeled amplitude values ​​of the wellbore parameters; is the actual amplitude value of the well bypass; i is the angle of the preferred seismic data.

[0053] If the seismic data is pre-stack gather data, its Should be related to the angle of incidence It is a one-to-one correspondence; if the seismic data is pre-stack angle-based stacking data, its It should correspond one-to-one with the set of angles superimposed; if the earthquake data is full-stack data, the rate of change It is a unique value. Select its maximum value. Establish standards for evaluating seismic data. Analyze the rate of change statistically from regional databases. Based on the selected value, determine the rate of change. The evaluation criteria.

[0054] Taking 20% ​​as an example, it is believed that If the data base for SAC discrimination is ≤20%, then the scoring criteria are shown in Table 1 below.

[0055] Table 1

[0056]

[0057] ② A2: Amplitude Variation Quality Assessment

[0058] Amplitude-related attributes are extracted from relevant seismic bodies. Top and bottom attribute maps are extracted for the target layer, and the quality of amplitude attributes is evaluated. The evaluation of amplitude attribute quality includes two aspects: the difference in seismic response between sand bodies and surrounding rocks, and the continuity of amplitude within the oil and gas reservoir / trap. The average score of these two aspects is used as the amplitude attribute quality evaluation score.

[0059] a) Evaluation of the seismic response differences between oil and gas reservoir / trap sand bodies and surrounding rocks: Through forward modeling analysis of actual drilled wells within the trap, the response criteria for seismic differences between the target layer sand bodies and surrounding rocks are determined. At the same time, determine the step size of the amplitude change value. This study establishes evaluation criteria for the differences in seismic response between oil and gas reservoir / trap sand bodies and surrounding rocks; based on the sedimentary model of the oil and gas reservoir / trap, it determines the search radius r of the surrounding rocks of the trap, which can be a constant or a variable value depending on the actual situation; and it uses the amplitude values ​​within the radius r of the oil and gas reservoir / trap as the evaluation criterion. The average amplitude within the loop is taken as ,calculate According to the scoring criteria (see...) Figure 2 ), and get a score.

[0060] b) Evaluate the amplitude continuity within the reservoir / trap area: Establish an evaluation standard for the amplitude attribute quality within the trap by calculating the ratio γ of the bright area value to the reservoir / trap area value (see [link]). Figure 3 ).

[0061] The average score of the two factors mentioned above is used as the evaluation score for the amplitude attribute quality.

[0062] ③ A3: Fluid Response Sensitivity Assessment

[0063] Based on the rock physics analysis of the drilled rocks in the target area, the amplitude differences between oil / gas layers and water layers were determined. Due to the differences in their geophysical properties, the seismic response was calculated through the differences in physical parameters to determine the amplitude curves of the oil / gas layer and water layer responses. The specific calculation formulas are as follows:

[0064]

[0065] In the formula, For a certain angle of incidence The corresponding amplitude value; A is the intercept, B is the gradient, C is the curvature; V p V s , The parameters vary based on the oil / gas reservoir and the water reservoir.

[0066] The calculated amplitude values ​​are extracted, and the cumulative rate of change of amplitude between the water layer and the oil / gas layer is calculated. The formula for its rate of change is as follows:

[0067]

[0068] In the formula, This represents the cumulative rate of change of oil / gas reservoir amplitude. The response amplitude value of the oil layer at a certain incident angle; This represents the amplitude value of the water layer response at a certain incident angle.

[0069] If the seismic data is pre-stack angle-based stacking data, its The values ​​should correspond one-to-one with the selected pre-stack angles. For example, if it is long-range stacked data (25°-36°), then N=25, M=36; if it is full-scale stacked data (0-30°), then N=0, M=30. The values ​​of M and N are determined according to the actual situation.

[0070] Cumulative rate of change A larger amplitude indicates a greater difference between the oil / gas and water layers, making the amplitude easier to identify. The maximum cumulative rate of change of amplitude for each well was statistically analyzed using a database. and minimum value Calculate the interval as the boundary. The evaluation criteria for fluid response sensitivity are shown in Table 2 below.

[0071] Table 2

[0072]

[0073] ④ Interpretation of fluid interfaces in target oil and gas reservoirs

[0074] Based on the aforementioned analyses ①-③, the possible fluid interface locations at amplitude variations within the study area are analyzed, including the interpretation of the top and bottom edges of seismic data, extraction of top and bottom attributes, and, combined with geological understanding of hydrocarbon accumulation and drilling results, the fluid interface depth Z is determined. i Prediction is performed. For a given oil group, there may be multiple potential fluid interface locations Z1, Z2…Z… i The following evaluation was conducted on all possible depth values ​​through analysis.

[0075] ⑤ A4: Construction of Amplitude Consistency Analysis (Conf)

[0076] The correlation between seismic attribute variation lines and structural isolines is analyzed. Generally, changes in fluid properties cause changes in wave impedance, resulting in amplitude changes near the fluid interface. Within oil and gas reservoirs, when the downdip edge of seismic attributes overlaps with structural isolines, it indicates the presence of a fluid interface to some extent. Based on the correlation between attribute variations and structural isolines, and combined with drilling data confirming the matching relationship between fluid interfaces and attributes in the study area, a consistency assessment standard suitable for this region is established (see...). Figure 4 Contour lines that are close to the property change lines and have a good overlap trend are selected as the predicted fluid interface values. These values ​​are then compared with regional assessment standards to guide the identification of fluid interface locations.

[0077] ⑥ A5: Top-bottom property fluid interface response consistency evaluation (TBC)

[0078] According to the layered model, both the top and bottom surfaces respond at the fluid interface, exhibiting characteristics of an oil-water / gas-water transition zone with weakened amplitude. Ideally, the fluid interface depths identified by the top and bottom surfaces of the target layer should be consistent, and fluid identification based on the agreement between the amplitude of the top or bottom surface and structural contour lines is feasible. However, in practice, the horizontal and vertical distribution range of the oil-water / gas-water transition zone varies due to the formation dip angle. When the formation dip angle is small, the oil-water / gas-water transition zone is longer, and the amplitude change is less significant, leading to some error in determining the fluid interface value based solely on a single layer. To minimize human error, a joint determination of fluid interface identification using top and bottom surface attributes is adopted. This is mainly based on the consistency analysis standard established in section ④, where the fluid interface depths determined after consistency analysis of the top and bottom surface attribute change lines and structural contour lines are picked up and compared; considering the influence of the oil-water / gas-water transition zone, a tolerance analysis is performed on the differences in fluid interface depth values ​​identified by the top and bottom surfaces. The relationship between the oil-water interface and the top and bottom surfaces is described in [reference needed]. Figure 5 .

[0079] By calculating the difference between the actual drilling depth of the oil / gas-water interface in the target area and the depth determined by the SAC at the top and bottom surfaces, a set of tolerance values ​​for this difference is established. Based on this set, a TBC evaluation standard is established. Tolerance Values Its fault tolerance value set is Take the minimum value in the set and maximum value The step size serves as the standard for this evaluation. The specific evaluation criteria are shown in Table 3 below.

[0080] Table 3

[0081]

[0082] ⑦ A6: Geology Match

[0083] The amplitude is also affected by various factors, such as changes in sand body thickness and porosity, and the boundaries of sand body distribution. Errors need to be eliminated based on actual conditions and a geological perspective. Based on regional geological and sedimentary analysis, the geological influencing factors in Table 4 below are evaluated, and the arithmetic mean is calculated to ultimately determine the geological fit score.

[0084] Table 4

[0085]

[0086] Weight (Q) calculation method:

[0087] Based on regional geological analysis, key factors and their associated wells were successfully matched using multivariate principal component analysis within the initially established database. For example... Figure 6 As shown, by statistically analyzing the key controlling factors, a diagram of key SAC factors and drilling success rate under the actual drilling fluid interface in the study area was established. The weights of each key factor were calculated using ROUND(drilling success rate of a certain key factor / 20,0) and quantified into scoring values, which were then plotted in a spider diagram (see...). Figure 7 The weighting percentage of key SAC factors related to the objective is determined, and the impact value Q is calculated. i (1≤Q i ≤5).

[0088] The method of assigning weights can be modified according to the actual geological conditions and the depth of exploration in the study area. For example, if the number of sample points in the study area is small, weights can be assigned based on empirical methods or equal weighting methods, according to drilled oil and gas reservoirs and comprehensive geological analysis.

[0089] SAC rating:

[0090] Based on the analysis of key factors and weights of the target area SAC, the calculation formula for SAC fluid interface evaluation is as follows:

[0091]

[0092] In the formula, A i The scores for each key factor; Q i The weighting factors for each key element are defined; n is set to 6 (this can be adjusted based on actual conditions). The scoring results for the target oil and gas reservoir are stored in the database and compared with the scores of other oil and gas reservoirs to verify their reasonableness. If reasonable, the score is adopted; otherwise, return to step ④ for re-evaluation.

[0093] For example, based on databases and practical experience, successful oil and gas reservoirs P have been discovered in the region. SAC When P = 0.5, then determine when P SAC When P > 0.5, the predicted fluid interface value is considered relatively reliable; if there are multiple predicted fluid interfaces, they should be calculated separately according to the evaluation process. SAC The maximum fluid interface value is considered to be the optimal fluid interface location in the study area.

[0094] Example 1

[0095] This embodiment provides a method for predicting the SAC fluid interface in lithologic oil and gas reservoirs in deep water areas with few wells. Taking the prediction of the oil-water interface in a target area as an example, the method includes the following steps:

[0096] ① A1: Data Quality Assessment

[0097] The target area possesses pre-stack angle-based stacking data and nearly ten years of completed well logging data. Comparing the forward-modeled seismic traces of the target area with actual earthquakes, the calculated amplitude variation rate is 5%, less than 10%, meeting the data requirements for using this method. Calculations show that... =3.5%, which meets the requirements, therefore it has a good foundation. According to the aforementioned scoring criteria, the reliability of the target area data is A1=5.

[0098] Figure 8 This is a comparison chart showing the difference between the actual earthquake amplitude and the forward modeling amplitude at the well site in this embodiment.

[0099] ② A2: Amplitude Variation Quality Assessment

[0100] a) Evaluate the differences in seismic response between oil and gas reservoir / trap sand bodies and surrounding rocks:

[0101] By using forward modeling during drilling, the response criteria for the difference between the target layer sand body and the surrounding rock in the seismic field were determined. If it is 0.15, then =0.2125, and the scoring criteria established based on this calculation are shown in Table 5 below.

[0102] Table 5

[0103]

[0104] For oil and gas reservoir traps Therefore, AV(1) = 4.

[0105] b) Evaluate the amplitude continuity within the reservoir / trap area:

[0106] Analysis of the seismic attributes interpreted in the target area showed that the predominantly bright red and yellow attributes within the traps were dominant. (See...) Figure 9 Area value (bright area) / Area value (overall enclosure) ratio =0.78. According to the aforementioned scoring criteria, the target area's attribute quality rating is A2=4.

[0107] ③ A3: Fluid Response Sensitivity Assessment

[0108] Based on the rock physics analysis of the drilled wells in the target area, the amplitude differences between the oil-bearing and water-bearing layers were determined. Due to their different geophysical properties, the target oil-bearing layer in the target area exhibits a significant strong amplitude characteristic, while the water-bearing layer shows a markedly weaker characteristic. The cumulative amplitude variation rate from the drilled wells in the region was also analyzed. The range is between 15% and 60%, and the evaluation criteria for the fluid response sensitivity of the target area are established accordingly, as shown in Table 6 below.

[0109] Table 6

[0110]

[0111] Accumulated amplitude change rate of the target layer in the target area calculate, =45%, therefore, A3=4.

[0112] ④ Based on the property changes, the predicted fluid interface was determined to be 5400m, see [reference needed]. Figure 10 .

[0113] ⑤ A4: Construction of Amplitude Consistency Analysis (Conf)

[0114] An analysis of the consistency between the seismic attribute variation lines and structural contour lines in the target area revealed a good match at a depth of 5360. Based on the established scoring criteria, the structural contour lines and attribute variation lines exhibited consistent trends and similar shapes. The consistency score for this target area was A4=5.

[0115] ⑥ A5: Top-bottom property fluid interface response consistency evaluation (TBC)

[0116] Analysis indicates that the dip angle of the formation in the target area is less than or equal to 3°. Based on this, the depths of the top and bottom surfaces of all drilled oil-water interfaces in the target area are identified and analyzed. A fault-tolerant set for the target area is established, and the step size is calculated accordingly. The scoring criteria for the target area are then established, as shown in Table 7 below.

[0117] Table 7

[0118]

[0119] Amplitude attributes were extracted from the sensitive properties of the top and bottom surfaces of the target sand body within the target area. Based on the consistency standard established in section ④, the optimal fit values ​​between the fluid interface and structural contour lines on the top and bottom surfaces of the sand body were selected. The analysis determined the predicted fluid interface value for the top surface to be 5400m, and the predicted fluid interface value for the bottom surface to be 5397m. (See...) Figure 11 The difference value According to the target area statistical scoring standard established above, A5=5, and the predicted fluid interface value is the average of the top and bottom values, which is 5398.5m.

[0120] ⑦ A6: Geology Match

[0121] Based on regional sedimentary understanding and nearby drilling conditions, the target sediments in the target area are continuous, and the possibility of changes in physical properties and lithology at the fluid interface is relatively small. Seismic amplitude is mostly affected by fluid dynamics. Detailed evaluation criteria are shown in Table 8 below.

[0122] Table 8

[0123]

[0124] The average value obtained from comprehensive analysis is A6=3.4, which is consistent with the geological viewpoint of the fluid interface.

[0125] Weight (Q) calculation method:

[0126] Based on the analysis of drilled wells in the region, the influence of key SAC factors under the actual drilled fluid interface in the target area was analyzed, and the weight factors of the key factors were determined. (See attached...) Figure 12 .

[0127] Depend on Figure 12 We know that Q1=5, Q2=2, Q3=4, Q4=5, Q5=4, and Q6=3.

[0128] SAC rating:

[0129] Based on the aforementioned evaluation formula, its target area P SAC =0.75, while P is established in the database.SAC The minimum value is 0.5. This satisfies P. SAC Under the condition of >0.5, the predicted fluid interface value of 5398.5 is relatively reliable.

[0130] Subsequent drilling of the target revealed a fluid interface value of 5398m, consistent with the prediction.

[0131] Therefore, this invention provides a set of deep-water sedimentary systems based on SAC fluid interface identification technology. By establishing quantitative evaluation standards for key parameters that are indicative of the oil-gas-water interface, and integrating regional oil and gas reservoir characteristics and expert experience for comprehensive evaluation and scoring, it achieves accurate prediction of oil and gas reservoir fluid interfaces, fully exploits seismic information, solves the problem of fluid interface identification in the absence of actual drilling, and significantly reduces the difficulty of fluid interface prediction.

[0132] The applicant declares that the above embodiments are only for illustrating the present invention, and the influencing factors can also be varied, with changes possible for each step. The scoring criteria based on each influencing factor can also be changed according to the actual situation. Based on this technical process, any improvements, additions, or equivalent transformations made to individual steps or individual parameters and their evaluation criteria according to the present invention, as well as improvements to the final scoring formula, should not be excluded from the protection scope of the present invention.

Claims

1. A method for predicting the SAC fluid interface in deep-water, low-well lithologic oil and gas reservoirs, characterized in that, The prediction method includes the following steps: (1) Establish a database of fluid interface and drilling success rate based on the actual drilling fluid interface conditions in the study area or globally; (2) Based on the database obtained in step (1), the key factors affecting the fluid interface are determined by combining the regional oil and gas reservoir characteristics analysis and statistics and the exploration experience of the study area. The key factors include the reliability of seismic data, the quality of amplitude attributes, the fluid response sensitivity, the possible fluid interface, the consistency of structural amplitude, the consistency of top and bottom attributes and the degree of agreement with regional geological understanding. (3) Analyze and evaluate the categories of key factors obtained in step (2) and their respective degrees of influence, and establish the SAC scoring standard to guide the prediction of fluid interfaces; The evaluation of the degree of influence in step (3) includes: calculating the weights of each key factor and quantifying them into scores; the weight assignment method is modified according to the actual geological conditions and the depth of exploration in the study area; the calculation formula involved in the SAC scoring standard is: In the formula, A i The scores for each key factor; Q i The weighting factors for each key factor; n is 6; The SAC refers to the degree of agreement between structural contour lines and seismic attribute change lines.

2. The prediction method according to claim 1, characterized in that, The evaluation of the reliability of the seismic data includes: conducting forward modeling using parameters obtained from the wellbore, comparing the actual amplitude values ​​of the seismic well bypass with the forward modeled amplitude values ​​of the wellbore parameters, analyzing the amplitude preservation of the seismic data, and determining the applicability of the seismic amplitude; and extracting amplitude curves at various angles for different target layers and establishing a method for calculating the amplitude variation rate.

3. The prediction method according to claim 1, characterized in that, The evaluation of amplitude attribute quality includes: evaluating the differences in seismic response between oil and gas reservoir / trap sand bodies and surrounding rocks, and the amplitude continuity within the oil and gas reservoir / trap, and calculating the average score of these two factors as the evaluation score of amplitude attribute quality.

4. The prediction method according to claim 1, characterized in that, The evaluation of fluid response sensitivity includes: based on the physical analysis of drilled rocks in the target area, calculating the seismic response through differences in physical property parameters, and determining the amplitude curves of the response of oil / gas layers and water layers.

5. The prediction method according to claim 1, characterized in that, The prediction of possible fluid interfaces includes: analyzing the possible fluid interface locations at amplitude variations within the study area, and predicting the fluid interface depth based on geological understanding of oil and gas reservoirs and drilling results.

6. The prediction method according to claim 1, characterized in that, The analysis of structural amplitude consistency includes: analyzing the degree of agreement between earthquake attribute change lines and structural contour lines; selecting structural contour lines that are closer to the attribute change lines and have a better superposition trend as predicted fluid interface values; comparing them with regional assessment standards; and guiding the identification of fluid interface locations.

7. The prediction method according to claim 1, characterized in that, The evaluation of the consistency of top and bottom properties includes: picking up and comparing the fluid interface depths determined after analyzing the consistency between the top and bottom property change lines and the structural contour lines, and performing fault tolerance analysis.

8. The prediction method according to claim 1, characterized in that, The evaluation of the degree of agreement on regional geological understanding includes: based on regional geological analysis and sedimentary analysis, evaluating each geological influencing factor separately, and finally determining the score of geological agreement by calculating the arithmetic mean.

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