Advantageous reservoir prediction method, apparatus, device, storage medium and program product
By acquiring wellbore collapse and paleostress parameters and combining them with rock properties, a correlation was established between fracture connectivity index and the problem of inaccurate prediction of favorable reservoirs in newly explored areas, thus achieving higher prediction accuracy.
Patent Information
- Application Number
- CN202110314734.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-03-24
- Publication Date
- 2026-03-03
- Estimated Expiration
- 2041-03-24
AI Technical Summary
Existing technologies cannot accurately predict favorable reservoirs in newly explored areas, especially in areas with low drilling density and a lack of geological data.
By acquiring wellbore collapse parameters, paleostress parameters, and rock property parameters, current stress parameters and fracture parameters are determined, and the correlation of fracture connectivity index is established, thereby predicting favorable reservoirs.
It improves the accuracy of predicting favorable reservoirs in newly explored areas, and is applicable to areas with low drilling density and lack of geological data, enabling more accurate identification of the existence of favorable reservoirs.
Smart Images
Figure CN115130267B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of petroleum exploration technology, and in particular to a method, apparatus, equipment, storage medium, and program product for predicting favorable reservoirs. Background Technology
[0002] Favorable reservoirs are areas where oil and gas are enriched. Predicting and evaluating favorable reservoir distribution areas is the ultimate goal of reservoir research and a key to oil and gas exploration.
[0003] With the increasing intensity of oil and gas resource exploration and development, the focus has shifted from conventional reservoirs to unconventional reservoirs, with the exploration and development of ultra-deep favorable reservoirs becoming a current trend. Existing methods for predicting favorable reservoirs include well-seismic analysis, wellpoint constraint methods, and fractal geometry methods. However, these methods are only applicable to areas with high drilling density and complete geological data. Newly explored areas have low drilling density and lack geological data; therefore, existing methods cannot accurately predict favorable reservoirs in these areas. Summary of the Invention
[0004] This application provides a method, apparatus, equipment, storage medium, and program product for predicting favorable reservoirs, in order to solve the problem of the inability to accurately predict favorable reservoirs in newly explored areas.
[0005] In a first aspect, this application provides a method for predicting favorable reservoirs, the method comprising:
[0006] Obtain wellbore collapse parameters, paleostress parameters, and rock property parameters of at least one well in the area to be predicted;
[0007] The present stress parameters of the location to be predicted are determined based on the wellbore collapse parameters and rock property parameters, and the fracture parameters of the location to be predicted are determined based on the paleostress parameters.
[0008] The crack connectivity index at the location to be predicted is determined based on the current stress parameters and crack parameters.
[0009] The presence of a favorable reservoir at the predicted location is predicted based on the fracture connectivity index.
[0010] Optionally, determining the crack connectivity index at the location to be predicted based on the current stress parameters and crack parameters includes:
[0011] Obtain the first correlation between current stress parameters, crack parameters, and crack connectivity index;
[0012] The crack connectivity index of the location to be predicted is determined based on the first correlation, under the current stress and crack parameters.
[0013] Optionally, obtaining the first correlation between current stress parameters, crack parameters, and crack connectivity index includes:
[0014] Obtain the fracture parameters of each rock sample in multiple sets of rock samples;
[0015] By conducting triaxial compression tests on the multiple groups of rock samples, the compressive stress and fracture connectivity index of each group of rock samples were obtained.
[0016] The first correlation was determined based on the fracture parameters, compressive stress, and fracture connectivity index of each group of rock samples.
[0017] Optionally, predicting whether a favorable reservoir exists at the predicted location based on the fracture connectivity index includes:
[0018] Determine whether the crack connectivity index at the location to be predicted is greater than a preset crack connectivity index;
[0019] If the fracture connectivity index is greater than the preset fracture connectivity index, then a favorable reservoir exists at the predicted location.
[0020] Optionally, the method further includes:
[0021] Obtain wellbore collapse parameters for at least one well, determine multiple location points within a preset range from the location of the well, and obtain the stress coefficients corresponding to the multiple location points;
[0022] A second correlation is determined based on the wellbore collapse parameters of the at least one well and the stress coefficients corresponding to multiple location points; the second correlation is the correlation between the wellbore collapse parameters and the current stress coefficients.
[0023] Accordingly, the current stress parameters at the location to be predicted are determined based on the wellbore collapse parameters and rock property parameters, including:
[0024] The corresponding current stress coefficient is determined based on the second correlation and the wellbore collapse parameters;
[0025] The current stress parameters of the location to be predicted are determined based on the current stress coefficient and the rock property parameters.
[0026] Optionally, the method further includes:
[0027] Obtain at least one well's paleostress parameter and the corresponding fracture parameter;
[0028] A third correlation is determined based on the paleostress parameters and the corresponding crack parameters for each paleostress parameter; the third correlation is the correlation between the paleostress parameters and the crack parameters.
[0029] Accordingly, determining the crack parameters at the location to be predicted based on the paleostress parameters includes:
[0030] The crack parameters at the location to be predicted are determined based on the third correlation and the paleostress parameters.
[0031] Secondly, this application provides an advantageous reservoir prediction device, comprising:
[0032] The acquisition module is used to acquire wellbore collapse parameters, paleostress parameters, and rock property parameters of at least one well in the area to be predicted, as well as the location to be predicted in the area to be predicted.
[0033] The determination module is used to determine the current stress parameters of the location to be predicted based on the wellbore collapse parameters and rock property parameters, and to determine the fracture parameters of the location to be predicted based on the paleostress parameters.
[0034] The determining module is further configured to determine the crack connectivity index of the location to be predicted based on the current stress parameters and crack parameters.
[0035] The prediction module is used to predict whether a favorable reservoir exists at the location to be predicted based on the fracture connectivity index.
[0036] Thirdly, this application provides an advantageous reservoir prediction device, comprising:
[0037] Memory, used to store program instructions;
[0038] A processor for calling and executing program instructions in the memory to perform the method as described in any of the first aspects.
[0039] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the first aspects.
[0040] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the first aspects.
[0041] This application provides a method, apparatus, equipment, storage medium, and program product for predicting favorable reservoirs. The method includes: acquiring wellbore collapse parameters, paleostress parameters, and rock property parameters of at least one well in the area to be predicted; determining the present stress parameters of the location to be predicted based on the wellbore collapse parameters and rock property parameters; determining the fracture parameters of the location to be predicted based on the paleostress parameters; determining the fracture connectivity index of the location to be predicted based on the present stress parameters and fracture parameters; and predicting whether a favorable reservoir exists at the location to be predicted based on the fracture connectivity index. The solution of this application determines the fracture connectivity index under present stress by establishing a first correlation, and adds the influence of present stress on fractures in addition to considering fracture parameters, thus enabling a more reasonable and accurate prediction of favorable reservoirs. Attached Figure Description
[0042] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0043] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of the present invention;
[0044] Figure 2 A schematic flowchart of a favorable reservoir prediction method provided in an embodiment of the present invention;
[0045] Figure 3 A flowchart illustrating another advantageous reservoir prediction method provided in an embodiment of the present invention;
[0046] Figure 4 A schematic diagram of the advantageous reservoir prediction device provided in an embodiment of the present invention;
[0047] Figure 5 This is a schematic diagram of the structure of a favorable reservoir prediction device provided in an embodiment of the present invention. Detailed Implementation
[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0049] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0050] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of the present invention, such as... Figure 1 As shown, the executing entity of this invention can be a favorable reservoir prediction device, which is installed on a favorable reservoir prediction equipment. The device can be implemented in software or hardware. When determining a favorable reservoir, the favorable reservoir prediction device can first obtain wellbore collapse parameters and paleostress parameters, and then determine the fracture connectivity index based on geomechanical properties. The geomechanical properties indicate that the fracture connectivity index can be obtained from the wellbore collapse parameters and paleostress parameters. The fracture connectivity index reflects the intersection relationship between multiple fractures at the predicted location under current stress, and thus, the existence of a favorable reservoir can be predicted through the fracture connectivity index.
[0051] In some technologies, various methods can be used to determine whether a favorable reservoir exists in a predicted area, such as well-seismic combined analysis, well point constraint methods, and fractal geometry methods. However, these methods all have certain requirements for the predicted area, such as high drilling density and complete geological data. If the area is newly explored, these conditions cannot be met, and using these methods to predict the existence of favorable reservoirs in newly explored areas will result in inaccurate predictions. The accuracy of favorable reservoir prediction is related to the drilling rate, development cost, development efficiency, and stable supply of oil and gas resources. Therefore, it is necessary to improve the accuracy of favorable reservoir prediction in newly explored areas.
[0052] To address the aforementioned issues, this application provides a method for predicting favorable reservoirs. This method uses geomechanical techniques to predict favorable reservoirs, specifically by obtaining wellbore collapse parameters for the area to be predicted, determining the current stress based on these parameters, and determining the fracture connectivity index based on the established correlation between the current stress fracture parameters and the fracture connectivity index. This index represents the impact of the current stress on the fractures. By predicting favorable reservoirs based on fracture parameters, this method can more accurately predict favorable reservoirs in newly explored areas.
[0053] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.
[0054] Figure 2 This is a schematic flowchart of the favorable reservoir prediction method provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the method in this embodiment may include:
[0055] Step S201: Obtain the wellbore collapse parameters of at least one well in the area to be predicted, the paleostress parameters of the location to be predicted in the area to be predicted, and the rock property parameters.
[0056] The area to be predicted refers to an oil and gas field. For a newly explored oil and gas field, there should be at least one well. The wellbore collapse parameters of the well are obtained, and the obtained wellbore collapse parameters can be used as the wellbore collapse parameters for the entire area to be predicted.
[0057] When multiple wells exist, the wellbore collapse parameters of multiple wells are obtained. When predicting favorable reservoirs at the location to be predicted, the wellbore collapse parameters of the well closest to the location to be predicted can be used as the wellbore collapse parameters of the location to be predicted; or the wellbore collapse parameters of multiple wells within a preset range from the location to be predicted can be calculated to obtain the average wellbore collapse parameters, and the obtained average wellbore collapse parameters can be used as the wellbore collapse parameters of the location to be predicted.
[0058] Understandably, when there are multiple wells, the more accurate the wellbore collapse parameters obtained at the location to be predicted, the more accurate the prediction of favorable reservoirs will be.
[0059] In this embodiment, the wellbore collapse parameters mainly include two parameters: the wellbore collapse depth and the angle between the wellbore collapse edge and the direction of minimum horizontal stress. The wellbore collapse depth is positively correlated with the collapse thickness, and the angle between the wellbore collapse edge and the direction of minimum horizontal stress is positively correlated with the collapse range.
[0060] The positive correlation indicates that the greater the thickness of the collapse, the greater the wellbore collapse depth, and the smaller the thickness of the collapse, the smaller the wellbore collapse depth. Furthermore, the larger the collapse area, the greater the angle between the wellbore collapse edge and the direction of minimum horizontal stress, and the smaller the collapse area, the smaller the angle between the wellbore collapse edge and the direction of minimum horizontal stress.
[0061] In this embodiment, the paleostress parameters at the location to be predicted can be obtained through acoustic emission experiments conducted on the region to be predicted. Here, paleostress represents the stress at which the crack formed at the location to be predicted. In other words, the current crack at the location to be predicted is based on the paleostress.
[0062] The stress parameters include the magnitude and direction of the stress. The magnitude of the stress can include three normal stresses and one shear stress. The three normal stresses represent the magnitude of the stress component in the positive direction of the three-dimensional coordinate system, and the shear stress represents the magnitude of the stress component tangential to the cross-section. Therefore, the paleostress parameters include both the magnitude and direction of the paleostress.
[0063] In this embodiment, the rock property parameters at the location to be predicted include the longitudinal wave, transverse wave, density, and depth of the rock at that location. These parameters will change at different locations, causing changes in the current stress parameters; therefore, it is necessary to obtain these parameters.
[0064] S202. Determine the current stress parameters of the location to be predicted based on the wellbore collapse parameters and rock property parameters, and determine the fracture parameters of the location to be predicted based on the paleostress parameters.
[0065] Currently, oil and gas resource exploration and development is trending towards the development of deep reservoirs. Due to their large burial depth, high formation pressure coefficient, multiple and intense tectonic movements, and highly developed natural fractures, deep reservoirs have become important reservoir spaces and seepage channels. Therefore, favorable reservoirs can be identified by searching for fractures.
[0066] The current stress parameters are influenced by wellbore collapse parameters and rock property parameters, and there is a certain correlation between them. Therefore, after obtaining the wellbore collapse parameters and rock property parameters, the current stress parameters at the location to be predicted can be determined.
[0067] The crack parameters, used to characterize crack development, can include crack density, crack aperture, and crack length. Crack density can be volume density, surface density, or linear density, representing mass per unit volume, mass per unit area, and mass per unit length, respectively. Crack aperture characterizes the crack width, and crack length characterizes the distance the crack extends.
[0068] There is also a correlation between paleostress parameters and crack parameters. For a given paleostress, the corresponding crack parameters can be determined.
[0069] S203. Determine the crack connectivity index at the location to be predicted based on the current stress parameters and crack parameters.
[0070] Since fracture parameters can characterize fracture development, favorable reservoirs can be predicted based on these parameters. For example, a high fracture density, large fracture aperture, and large fracture depth at the predicted location indicate a higher probability of a favorable reservoir. However, fracture evaluation depends not only on the individual fracture parameters but also on the degree of intersection between fractures. If two sets of fractures contain three fractures, and the first set has no intersections while the second set has multiple intersections, then the first set is less developed than the second set.
[0071] Therefore, the concept of crack connectivity index is introduced here to evaluate the degree of correlation between cracks. It can be calculated using the crack parameters of each crack and the number of intersections between cracks. A higher crack connectivity index indicates a higher degree of correlation between cracks; a lower crack connectivity index indicates a lower degree of correlation between cracks.
[0072] Current stress can alter the crack parameters of individual cracks and the number of intersections between cracks, thus changing the crack connectivity index. Specifically, when a crack is subjected to current stress, its development changes. When a crack is subjected to a force perpendicular to its extension direction (i.e., the crack length direction), the crack aperture decreases, and the change in crack size is positively correlated with the magnitude of the stress. When a crack is subjected to a force parallel to its extension direction, the crack aperture increases, and the change in crack size is also positively correlated with the magnitude of the stress.
[0073] The crack connectivity index is related to crack parameters and current stress. Therefore, after obtaining the current stress and crack parameters, the corresponding crack connectivity index can be obtained.
[0074] S204. Predict whether there is a favorable reservoir at the location to be predicted based on the fracture connectivity index.
[0075] After obtaining the fracture connectivity index, favorable reservoirs can be predicted based on the fracture connectivity index. Specifically, predictions can be made directly based on the fracture connectivity index, or the fracture connectivity index can be combined with other values to determine whether a favorable reservoir exists.
[0076] In this embodiment of the invention, favorable reservoirs are predicted using geomechanical methods. Specifically, wellbore collapse parameters for the area to be predicted are obtained, and current stress parameters are determined based on these parameters. The fracture connectivity index, which represents the impact of current stress on fractures, is then determined based on the established correlation between current stress parameters, fracture parameters, and fracture connectivity index. This method has two advantages: firstly, it can predict favorable reservoirs in the area to be predicted by obtaining only wellbore collapse parameters, making it suitable for newly explored areas; secondly, the calculated fracture connectivity index can simultaneously reflect the impact of fracture parameters and current stress parameters on fractures, enabling more accurate prediction of favorable reservoirs in newly explored areas.
[0077] Figure 3 This is a schematic flowchart illustrating another advantageous reservoir prediction method provided in an embodiment of the present invention. Figure 3 As shown, the method in this embodiment may include:
[0078] Step S301: Obtain the wellbore collapse parameters of at least one well in the area to be predicted, the paleostress parameters of the location to be predicted in the area to be predicted, and the rock property parameters.
[0079] The execution process of step S301 is the same as that of step S201. For details, please refer to the above embodiments, which will not be repeated here.
[0080] Step S302: Determine the current stress parameters of the location to be predicted based on the wellbore collapse parameters and rock property parameters, and determine the fracture parameters of the location to be predicted based on the paleostress parameters.
[0081] The execution process of step S302 is the same as that of step S202. For details, please refer to the above embodiments, which will not be repeated here.
[0082] Step S303: Obtain the first correlation between current stress parameters, crack parameters and crack connectivity index.
[0083] In this embodiment, before determining the crack connectivity index, it is necessary to first obtain the first correlation between the current stress parameters, crack parameters and crack connectivity index.
[0084] The method for determining the first association relationship can be as follows:
[0085] Optionally, obtaining the first correlation between current stress parameters, crack parameters, and crack connectivity index includes:
[0086] The crack parameters of each rock sample in a set of multiple rock samples are obtained; the compressive stress and crack connectivity index of each rock sample are obtained by conducting a triaxial compression test on the multiple rock samples; the first correlation relationship is determined based on the crack parameters, compressive stress and crack connectivity index of each rock sample.
[0087] Based on observations of multiple sets of acquired rock samples, fracture parameters, such as fracture density, fracture aperture, and fracture depth, are obtained; the rock samples are obtained from the locations to be predicted. Specifically, the fracture parameters of the rock samples can be obtained through microscopic thin-section observation or CT 3D fracture modeling.
[0088] After obtaining the fracture parameters under stress-free conditions, triaxial compression experiments (compression experiments in the positive direction of a three-dimensional coordinate system) were conducted on each group of rock samples to obtain the fracture parameters and the number of fracture intersections under stress. The fracture connectivity index was then calculated based on these parameters and the number of intersections. Specifically, this can be achieved by weighting the fracture parameters and the number of intersections. Finally, the fracture parameters, compressive stress, and fracture connectivity index for each group of rock samples under stress-free conditions can be obtained, and correlations can be established based on these values. The first correlation is between the fracture connectivity index and the fracture parameters and the current stress parameters; that is, when at least one of the fracture parameters or the current stress parameters changes, the fracture connectivity index changes.
[0089] The form in which the first association is represented is not limited; it can be a correspondence table, a calculation formula, a graph, etc.
[0090] Step S304: Determine the crack connectivity index of the location to be predicted under the current stress parameters and crack parameters based on the first correlation relationship.
[0091] After obtaining the first correlation, the corresponding crack connectivity index can be found based on the current stress parameters and crack parameters of the location to be predicted. For example, when the first correlation is a correspondence table, the crack connectivity index can be obtained by looking up the table; when the first correlation is a calculation formula, the crack connectivity index can be obtained by calculation; when the first correlation is a curve, the crack connectivity index can be obtained by querying the graph.
[0092] The obtained crack connectivity index is the crack connectivity index of the location to be predicted.
[0093] Introducing the concept of fracture connectivity index allows for a better assessment of fracture development. Furthermore, establishing a primary correlation can facilitate the quick and easy determination of the fracture connectivity index.
[0094] Step S305: Determine whether the crack connectivity index at the location to be predicted is greater than the preset crack connectivity index.
[0095] In this embodiment, after determining the fracture connectivity index at the location to be predicted, the presence of a favorable reservoir can be determined based on the fracture connectivity index. Specifically, a higher fracture connectivity index indicates a better degree of fracture development, thus indicating the presence of a favorable reservoir; conversely, a lower fracture connectivity index indicates a poor degree of fracture development, thus indicating the absence of a favorable reservoir. Therefore, a preset fracture connectivity index can be set, and the obtained fracture connectivity index can be compared with the preset fracture connectivity index to determine whether a favorable reservoir exists.
[0096] The pre-crack connectivity index can be set according to the actual situation, and no specific value is limited here.
[0097] Step S306: If the fracture connectivity index is greater than the preset fracture connectivity index, then there is a favorable reservoir at the location to be predicted.
[0098] If the obtained fracture connectivity index is greater than the preset fracture connectivity index, then a favorable reservoir exists at the predicted location; conversely, if the obtained fracture connectivity index is less than or equal to the preset fracture connectivity index, then a favorable reservoir does not exist at the predicted location. For example, if the obtained fracture connectivity index is 10 and the preset fracture connectivity index is 7, then a favorable reservoir exists at the predicted location.
[0099] By comparing the obtained fracture connectivity index with the preset connectivity index, it is possible to intuitively determine whether there is a favorable reservoir at the predicted location.
[0100] The process of determining current stress parameters and crack parameters is explained in detail below.
[0101] Optionally, the method further includes:
[0102] Obtain wellbore collapse parameters for at least one well, determine multiple location points within a preset range from the location of the well, and obtain the stress coefficients corresponding to the multiple location points;
[0103] A second correlation is determined based on the wellbore collapse parameters of the at least one well and the stress coefficients corresponding to multiple location points; the second correlation is the correlation between the wellbore collapse parameters and the current stress coefficients.
[0104] Accordingly, the current stress parameters at the location to be predicted are determined based on the wellbore collapse parameters and rock property parameters, including:
[0105] The corresponding current stress coefficient is determined based on the second correlation and the wellbore collapse parameters;
[0106] The current stress parameters of the location to be predicted are determined based on the current stress coefficient and the rock property parameters.
[0107] In this embodiment, the current stress parameter is related to the current stress coefficient and the rock property parameters at the location to be predicted. The current stress coefficient is further correlated with the wellbore collapse parameters. Therefore, it is necessary to first establish the correlation between the wellbore collapse parameters and the current stress coefficient, i.e., the second correlation.
[0108] This can be achieved by acquiring wellbore collapse parameters from at least one well, then determining multiple location points within a preset range from the well location, and acquiring stress parameters at these multiple location points. Next, the rock properties at each location point are acquired, and the stress coefficient at each location point is determined based on the stress parameters and corresponding rock properties.
[0109] After obtaining the wellbore collapse parameters and stress coefficients at multiple locations, a second correlation is established. The form of this second correlation is not limited; it can be a correspondence table, calculation formula, graph, etc. When the wellbore collapse parameters differ, the stress coefficients at different locations will also differ.
[0110] After determining the second correlation, the current stress parameters can be determined. Specifically, the current stress coefficient can be obtained by querying the second correlation based on the acquired wellbore collapse parameters, and then the stress parameters can be obtained based on the rock property parameters of the location to be predicted. For example, the current stress parameters and rock property parameters can be multiplied to obtain the current stress.
[0111] By establishing a second correlation, it becomes easier to obtain the current stress parameters at the location to be predicted.
[0112] Optionally, the method further includes:
[0113] Obtain at least one well's paleostress parameter and the corresponding fracture parameter;
[0114] A third correlation is determined based on the paleostress parameters and the corresponding crack parameters for each paleostress parameter; the third correlation is the correlation between the paleostress parameters and the crack parameters.
[0115] Accordingly, determining the crack parameters at the location to be predicted based on the paleostress parameters includes:
[0116] The crack parameters at the location to be predicted are determined based on the third correlation and the paleostress parameters.
[0117] Similarly, in this embodiment, it is also necessary to obtain the crack parameters, that is, the crack parameters under no stress. There is a correlation between the crack parameters and the paleostress parameters, namely the third correlation. Therefore, when determining the crack parameters, the third correlation can be determined first, and then the crack parameters can be obtained based on the paleostress parameters at the location to be predicted.
[0118] This involves obtaining paleostress parameters around the wellbore, specifically through acoustic emission experiments. Simultaneously, fracture parameters, such as fracture density, fracture aperture, and fracture depth, need to be obtained through observational experiments.
[0119] After obtaining the above values, the correlation between paleostress parameters and crack parameters can be established. The form of this third correlation is not limited; it can be a correspondence table, a calculation formula, a graph, etc. For example, a correspondence table can be created between each paleostress parameter and its corresponding crack parameter, or a graph can be plotted, or a calculation formula can be generated.
[0120] After obtaining the third correlation, the corresponding crack parameters can be found based on the paleostress parameters of the location to be predicted.
[0121] The above method can facilitate the acquisition of crack parameters at the location to be predicted by establishing a third correlation.
[0122] In practice, first, second, and third correlations can be established in advance. When predicting favorable reservoirs at the location to be predicted, wellbore collapse parameters, paleostress parameters, and rock property parameters at the location to be predicted can be directly obtained. The established correlations can then be used to further determine the fracture connectivity index and predict favorable reservoirs at the location to be predicted.
[0123] Due to the low drilling density in new exploration areas and the lack of an effective method for predicting favorable reservoirs, the favorable reservoir prediction method proposed in this invention can predict favorable reservoirs with less data. Furthermore, this method considers the influence of current stress on fracture development and has high prediction accuracy. It can effectively solve the problems faced by well deployment in new exploration areas or oilfields with poor geological data.
[0124] Figure 4 This is a schematic diagram of the advantageous reservoir prediction device provided in an embodiment of the present invention. Figure 4 As shown, the favorable reservoir prediction device 40 of this embodiment may include: an acquisition module 401, a determination module 402, and a prediction module 403.
[0125] The acquisition module 401 is used to acquire wellbore collapse parameters, paleostress parameters, and rock property parameters of at least one well in the area to be predicted, as well as the location to be predicted in the area to be predicted.
[0126] The determination module 402 is used to determine the current stress parameters of the location to be predicted based on the well wall collapse parameters and rock property parameters, and to determine the fracture parameters of the location to be predicted based on the paleostress parameters.
[0127] The determining module 402 is further configured to determine the crack connectivity index of the location to be predicted based on the current stress parameters and crack parameters.
[0128] The prediction module 403 is used to predict whether there is a favorable reservoir at the location to be predicted based on the fracture connectivity index.
[0129] Optionally, the determining module 402 includes a first determining unit, used for:
[0130] Obtain the first correlation between current stress parameters, crack parameters, and crack connectivity index;
[0131] The crack connectivity index of the location to be predicted is determined based on the first correlation, under the current stress and crack parameters.
[0132] Optionally, when the first determining unit obtains the first correlation between the current stress parameters, crack parameters, and crack connectivity index, it is specifically used for:
[0133] Obtain the fracture parameters of each rock sample in multiple sets of rock samples;
[0134] By conducting triaxial compression tests on the multiple groups of rock samples, the compressive stress and fracture connectivity index of each group of rock samples were obtained.
[0135] The first correlation was determined based on the fracture parameters, compressive stress, and fracture connectivity index of each group of rock samples.
[0136] Optionally, the prediction module 403 is specifically used for:
[0137] Determine whether the crack connectivity index at the location to be predicted is greater than a preset crack connectivity index;
[0138] If the fracture connectivity index is greater than the preset fracture connectivity index, then a favorable reservoir exists at the predicted location.
[0139] Optionally, the determining module 402 further includes a second determining unit, used for:
[0140] Obtain wellbore collapse parameters for at least one well, determine multiple location points within a preset range from the location of the well, and obtain the stress coefficients corresponding to the multiple location points;
[0141] A second correlation is determined based on the wellbore collapse parameters of the at least one well and the stress coefficients corresponding to multiple location points; the second correlation is the correlation between the wellbore collapse parameters and the current stress coefficients.
[0142] Accordingly, when determining the current stress parameters of the location to be predicted based on the wellbore collapse parameters and rock property parameters, the second determining unit is specifically used for:
[0143] The corresponding current stress coefficient is determined based on the second correlation and the wellbore collapse parameters;
[0144] The current stress parameters of the location to be predicted are determined based on the current stress coefficient and the rock property parameters.
[0145] Optionally, the determining module 402 further includes a third determining unit, used for:
[0146] Obtain at least one well's paleostress parameter and the corresponding fracture parameter;
[0147] The third correlation is determined based on the paleostress parameters and the corresponding crack parameters for each paleostress parameter; the third correlation is the correlation between the paleostress parameters and the crack parameters.
[0148] Accordingly, when determining the crack parameters at the location to be predicted based on the paleostress parameters, the third determining unit is specifically used for:
[0149] The crack parameters at the location to be predicted are determined based on the third correlation and the paleostress parameters.
[0150] The advantageous reservoir prediction device provided in this embodiment of the invention can achieve the above-mentioned... Figure 2 and Figure 3 The favorable reservoir prediction method shown in the embodiment has a similar implementation principle and technical effect, and will not be described again here.
[0151] Figure 5 This is a schematic diagram of the hardware structure of a favorable reservoir prediction device provided in an embodiment of the present invention. Figure 5 As shown, the advantageous reservoir prediction device 50 provided in this embodiment includes at least one processor 501 and a memory 502. The processor 501 and the memory 502 are connected via a bus 503.
[0152] In a specific implementation, at least one processor 501 executes computer execution instructions stored in the memory 502, causing at least one processor 501 to execute the favorable reservoir prediction method in the above method embodiment.
[0153] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.
[0154] In the above Figure 5 In the illustrated embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.
[0155] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage.
[0156] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.
[0157] This invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the advantageous reservoir prediction method described in the above-described method embodiments.
[0158] The aforementioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.
[0159] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.
[0160] One embodiment of this application provides a computer program product, including a computer program that, when executed by a processor, implements the features described in this application. Figure 2 and Figure 3 The favorable reservoir prediction method provided in any of the corresponding embodiments.
[0161] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.
Claims
1. A method of favorable reservoir prediction applied to new exploration areas, characterized in that, The method comprises: obtaining a borehole collapse parameter of at least one well in a to-be-predicted region, a paleostress parameter of a to-be-predicted position in the to-be-predicted region, and a rock property parameter; determining a present stress parameter of the to-be-predicted position according to the borehole collapse parameter and the rock property parameter, and determining a fracture parameter of the to-be-predicted position according to the paleostress parameter; obtaining a fracture parameter of each of a plurality of groups of rock samples; obtaining a compression stress corresponding to each of the plurality of groups of rock samples and a fracture connectivity index determined based on the fracture parameter of each fracture and the number of fracture intersection points by simulating the present stress state through triaxial compression experiments on the plurality of groups of rock samples; determining a first correlation relationship between the present stress parameter, the fracture parameter, and the fracture connectivity index according to the fracture parameter, the compression stress, and the fracture connectivity index corresponding to each of the plurality of groups of rock samples; wherein the rock samples are obtained from the to-be-predicted position; determining a fracture connectivity index of the to-be-predicted position under the present stress parameter and the fracture parameter of the to-be-predicted position according to the first correlation relationship; predicting whether a favorable reservoir exists in the to-be-predicted position according to the fracture connectivity index.
2. The method of claim 1, wherein, The method for predicting whether a favorable reservoir exists in the to-be-predicted position according to the fracture connectivity index comprises: determining whether the fracture connectivity index of the to-be-predicted position is greater than a preset fracture connectivity index; if the fracture connectivity index is greater than the preset fracture connectivity index, it is determined that a favorable reservoir exists in the to-be-predicted position.
3. The method according to any of claims 1-2, characterized in that, The method further comprises: obtaining a borehole collapse parameter of at least one well, determining a plurality of position points within a preset range from a position where the well is located, and obtaining a stress coefficient corresponding to each of the plurality of position points; determining a second correlation relationship according to the borehole collapse parameter of the at least one well and the stress coefficient corresponding to each of the plurality of position points; the second correlation relationship is a correlation relationship between the borehole collapse parameter and a present stress coefficient; correspondingly, determining a present stress parameter of the to-be-predicted position according to the borehole collapse parameter and the rock property parameter comprises: determining a corresponding present stress coefficient according to the second correlation relationship and the borehole collapse parameter; determining the present stress parameter of the to-be-predicted position according to the present stress coefficient and the rock property parameter.
4. The method according to any one of claims 1-2, characterized in that, The method further comprises: obtaining a paleostress parameter of at least one well and a fracture parameter corresponding to the paleostress parameter; determining a third correlation relationship according to the paleostress parameter and the fracture parameter corresponding to each of the paleostress parameters; the third correlation relationship is a correlation relationship between the paleostress parameter and the fracture parameter; correspondingly, determining a fracture parameter of the to-be-predicted position according to the paleostress parameter comprises: determining the fracture parameter of the to-be-predicted position according to the third correlation relationship and the paleostress parameter.
5. A means of favorable reservoir prediction applied to a new exploration area, characterized in that, The method comprises: obtaining a borehole collapse parameter of at least one well in a to-be-predicted region, a paleostress parameter of a to-be-predicted position in the to-be-predicted region, and a rock property parameter; determining a present stress parameter of the to-be-predicted position according to the borehole collapse parameter and the rock property parameter, and determining a fracture parameter of the to-be-predicted position according to the paleostress parameter; The determining module is further configured to determine a fracture connectivity index of the to-be-predicted location according to the present stress parameter and the fracture parameter; The predicting module is configured to predict whether a favorable reservoir exists in the to-be-predicted location according to the fracture connectivity index. The determining module comprises a first determining unit configured to: acquire fracture parameters of each group of rock samples in a plurality of groups of rock samples; simulate the present stress state through triaxial compression experiments on the plurality of groups of rock samples, acquire a compression stress corresponding to each group of rock samples and a fracture connectivity index determined based on the fracture parameters of each fracture and the number of fracture intersection points; determine a first correlation relationship between the present stress parameter, the fracture parameter and the fracture connectivity index according to the fracture parameters, the compression stress and the fracture connectivity index corresponding to each group of rock samples; wherein the rock samples are acquired from the to-be-predicted location; and determine the fracture connectivity index of the to-be-predicted location under the present stress parameter and the fracture parameter of the to-be-predicted location according to the first correlation relationship.
6. A favorable reservoir prediction device characterized by comprising: Comprising: a memory for storing program instructions; a processor for calling and executing the program instructions in the memory, and executing the method according to any one of claims 1-4.
7. A computer readable storage medium characterized by The computer readable storage medium stores computer execution instructions, and when the processor executes the computer execution instructions, the method according to any one of claims 1-4 is realized.
8. A program product, characterized by The computer program is characterized by comprising a computer program, which is executed by a processor to realize the method according to any one of claims 1-4.