Method for optimizing dosage of clay stabilizer in low-permeability tight reservoir

Abstract

The present application relates to the technical field of oil and gas field development and reservoir protection, and particularly relates to a low-permeability tight reservoir clay stabilizer dosage optimization method, first, the rock sample and different concentration gradient clay stabilizer solution are subjected to imbibition, the corresponding nuclear magnetic signal peak area at different imbibition time is obtained, the liquid intake rate K sequence and the permeability change rate delta K sequence are obtained; then the first weight coefficient alpha and the second weight coefficient beta are obtained; finally, the comprehensive decision index CDI sequence is calculated; the permeability change rate delta K is less than the maximum permeability damage threshold delta K max , and the concentration of the clay stabilizer solution corresponding to the minimum value of the comprehensive decision index CDI is the optimal clay stabilizer concentration; the present application realizes the precise and differentiated optimization of the clay stabilizer dosage, overcomes the shortcomings of the existing static evaluation method, and has important significance for protecting the low-permeability tight reservoir and improving the recovery rate.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development and reservoir protection, and particularly relates to a method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs. Background Art

[0002] High-content sensitive clay minerals, such as illite, illite / smectite mixed layer, etc., are commonly developed in low-permeability tight oil and gas reservoirs. During the processes of drilling, completion, fracturing reconstruction, injection and production development, the intrusion of external working fluids can easily induce physicochemical effects such as hydration swelling, dispersion and migration of clay minerals, resulting in the blockage of the microscopic pore-throat structure of the reservoir, a significant attenuation of the effective permeability, and ultimately severely restricting the productivity and development benefits of oil and gas wells. The industry standard "SY / T5358-2010 Evaluation Method for Reservoir Sensitivity Flow Experiments" provides an authoritative basis for grading the degree of water sensitivity damage for evaluating the sensitivity of the reservoir itself (for example, when the water sensitivity index Dw≤5% there is no damage, and when 5%<Dw≤30% there is weak damage, etc.).

[0003] Currently, the industry usually adopts the process technology of adding clay stabilizers to inhibit the reservoir damage caused by clay minerals. However, the existing evaluation methods and optimization strategies for stabilizer concentration still have the following key bottlenecks and cannot be fully integrated with the scientific evaluation system reflected by the above standards:

[0004] (1) Static evaluation dimension: The existing technologies mainly rely on static evaluation indexes such as anti-swelling rate test and endpoint permeability damage rate of core flow experiments, lacking the characterization of the dynamic processes of fluid intrusion, imbibition and damage evolution, and unable to reflect the real-time migration and interaction mechanism of working fluids in micro-nano pore throats, resulting in significant deviations in the determination of the critical concentration of stabilizers;

[0005] (2) Insufficient lithology adaptation ability: Low-permeability tight reservoirs have strong lithological and physical property heterogeneity. Different types of cores (such as fine sandstone, siltstone, mudstone, etc.) have essential differences in mineral composition, pore structure, clay occurrence state, etc., and there should be different requirements for stabilizer concentration. However, the current methods generally ignore the restrictive effect of reservoir geological characteristics and often provide single and empirical concentration recommendations, lacking a quantitative description of the lithology-concentration response relationship;

[0006] (3) Decision-making process relying on subjective experience: The existing concentration recommendations are mostly based on data provided by suppliers or field operation experience, lacking a standardized, reproducible and mechanism-clear experimental evaluation system that can be connected with standards such as "SY / T 5358-2010" as decision support, easily leading to the deviation of the dosing concentration from the optimal range, resulting in insufficient stabilization or excessive injection of chemical agents, not only unable to effectively protect the reservoir, but also may induce secondary damage and significantly increase the development cost.

[0007] Therefore, there is an urgent need in this field to develop a method for optimizing the dosage of clay stabilizers that can simulate real formation environments, characterize fluid dynamics and seepage behavior in real time, and integrate multi-source geological information. This will establish a scientific, accurate, and universally applicable concentration decision-making paradigm that aligns with industry standards, providing key technical support for the efficient and safe development of low-permeability tight reservoirs. Summary of the Invention

[0008] The purpose of this invention is to overcome the aforementioned deficiencies of existing technologies and provide a method for optimizing the dosage of clay stabilizers in low-permeability tight reservoirs based on dynamic permeation characterization. This method uses nuclear magnetic resonance (NMR) technology to monitor the entire permeation process in real time and innovatively proposes the dynamic evaluation parameter of "fluid inflow change rate," thereby achieving precise and scientific optimization of the clay stabilizer dosage for reservoirs of different lithologies.

[0009] The technical solution of this invention is as follows:

[0010] A method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs is as follows:

[0011] Rock samples were subjected to percolation with clay stabilizer solutions of varying concentrations. The peak areas of the nuclear magnetic resonance (NMR) signals at different percolation times were obtained, leading to the acquisition of the percolation rate change (K-series) and permeability change (ΔK-series) for different concentration gradient clay stabilizer solutions. Based on the mean, standard deviation, and coefficient of variation of the percolation rate change (K-series) and permeability change (ΔK-series), the first weighting coefficient α and the second weighting coefficient β were obtained. Furthermore, the comprehensive decision index (CDI) sequence for different concentration gradient clay stabilizer solutions was calculated. The condition was that the permeability change rate (ΔK) ≤ the maximum permeability damage threshold (ΔK). max Furthermore, the concentration of the clay stabilizer solution corresponding to the minimum value of the comprehensive decision index CDI is the optimal clay stabilizer concentration;

[0012] The specific solution process for the comprehensive decision index CDI is as follows:

[0013] CDI = α(K / K0) + β(△K / △K) max Formula 1

[0014] In the formula: α is the first weighting coefficient; β is the second weighting coefficient;

[0015] K is the rate of change of liquid inlet volume; K0 is the rate of change of liquid inlet volume when the concentration of clay stabilizer solution is 0.

[0016] △K represents the rate of change in permeability; △K max This represents the maximum penetration damage threshold.

[0017] The specific solution process for the first weighting coefficient α and the second weighting coefficient β is as follows:

[0018] α=CVK / (CV K +CV △K Equation 2

[0019] β=CV △K / (CV K +CV △K Equation 3

[0020] CV K =σ K / μ K Formula 4

[0021] CV △K =σ △K / μ △K Formula 5

[0022] Where: CV K σ is the coefficient of variation of the rate of change of the influent volume K; K μ K These are the standard deviation and mean of the rate of change of liquid inflow K, respectively;

[0023] CV △K σ is the coefficient of variation of the rate of change in permeability ΔK; △K μ △K These are the standard deviation and mean of the permeability change rate ΔK, respectively.

[0024] The specific solution process for the rate of change of liquid inflow K is as follows:

[0025] K=[(A tmax -A dry )-(A tcritical -A dry )] / (A tmax -A dry Formula 6

[0026] In the formula: A dry The peak area of ​​the nuclear magnetic resonance signal of the rock sample before infiltration; A tmax The peak area of ​​the NMR signal at the osmotic stability time point tmax; A tcritical The peak area of ​​the NMR signal at a specific time point tcritical during the initial stage of infiltration.

[0027] The different concentration gradients are specifically 0%, 0.1%, 0.3%, 0.5%, 0.7%, and 1.0%; the different absorption times are specifically 0h, 2h, 6h, 12h, 24h, 48h, and 72h.

[0028] Wherein, the initial specific time point tcritical of the permeation is 2 hours after the start of permeation, and the stable time point tmax of permeation is 72 hours after the start of permeation.

[0029] The specific solution process for the permeability change rate ΔK is as follows:

[0030] △K=|K0-K i | / K0×100% Formula 7

[0031] Where: K i This represents the permeability at a certain point in time after the start of osmosis.

[0032] Wherein, the maximum penetration damage threshold △K max It is 30%.

[0033] The technical advantages of this invention are as follows:

[0034] This invention constructs a comprehensive decision index (CDI) that combines the rate of change in influent volume (K) with the rate of change in permeability (ΔK). An increase in the rate of change in influent volume (K) reflects that the clay stabilizer has slowed the initial fluid intake process and inhibited rapid clay hydration and swelling; a decrease in the rate of change in permeability (ΔK) indicates reduced permeability damage and protection of reservoir seepage capacity. This invention achieves precise and differentiated optimization of clay stabilizer dosage, overcoming the shortcomings of existing static evaluation methods, and is of great significance for protecting low-permeability tight reservoirs and improving oil recovery. Attached Figure Description

[0035] Figure 1 This is a flowchart of the method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to the present invention. Detailed Implementation

[0036] A method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs is as follows.

[0037] The rock samples were subjected to percolation with clay stabilizer solutions of varying concentrations; the concentrations of the clay stabilizer solutions were 0%, 0.1%, 0.3%, 0.5%, 0.7%, and 1.0%.

[0038] The peak areas of nuclear magnetic resonance (NMR) signals were obtained at 0h, 2h, 6h, 12h, 24h, 48h, and 72h after the start of infiltration. The peak area of ​​the NMR signal at 0h is the peak area A of the rock sample before infiltration. dry Let A be the peak area of ​​the NMR signal corresponding to 2h. tcritical Let A be the peak area of ​​the NMR signal corresponding to 72h. tmax ;

[0039] The K-series of influent change rate and ΔK-series of permeability change rate were obtained by calculating the peak area of ​​the NMR signal at different times of infiltration for clay stabilizer solutions with different concentration gradients.

[0040] Based on the mean, standard deviation, and coefficient of variation of the liquid inflow rate change K sequence and the permeability change rate ΔK sequence, the first weighting coefficient α and the second weighting coefficient β are calculated.

[0041] Then, the CDI (Comprehensive Decision Index) sequence corresponding to clay stabilizer solutions with different concentration gradients was calculated.

[0042] With the rate of change in permeability ΔK ≤ the maximum permeability damage threshold ΔK max Furthermore, the concentration of the clay stabilizer solution corresponding to the minimum value of the comprehensive decision index CDI is the optimal clay stabilizer concentration.

[0043] Specific experimental cases

[0044] A method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs is as follows.

[0045] Step 1: Drill standard core columns (2.5 cm in diameter, 5.0 cm in length) from the core section of the low-permeability tight reservoir in the target oilfield. After chloroform extraction and washing with ethanol to remove salt, the standard core columns are dried to constant weight in a constant-temperature drying oven at 60-80℃ to obtain rock samples. The following steps are used for lithological classification:

[0046] Analyze well logging data from this area to obtain the natural gamma ray (GR) values ​​at corresponding depths in the core samples; analyze the grain size distribution of the core samples using a cast thin section and image analysis system; and accurately classify the core samples according to lithological classification standards.

[0047] Fine sandstone: GR value = 38 API, median grain size 0.12 mm (>0.0625 mm), thin section analysis shows a fine sand content of 68%;

[0048] Siltstone: GR value = 62 API, median grain size 0.045 mm (0.0156-0.0625 mm), silt content 63%;

[0049] Shale: GR value = 104 API, median grain size 0.008 mm (<0.0156 mm), mud content 58%.

[0050] The subsequent steps will all use mudstone and shale as an example.

[0051] Step 2: Preparation of clay stabilizers with different concentration gradients;

[0052] Commercially available quaternary ammonium salt clay stabilizers were selected, and their performance was tested in the laboratory as follows:

[0053] Molecular weight: 850 Daltons (meets the requirement of <1000 Daltons);

[0054] Anti-expansion rate: 94% (meets the requirement of ≥85%);

[0055] Temperature resistance: 155℃ (meets ≥140℃ requirements);

[0056] Three-wash erosion resistance: 96% (meets ≥90% requirement);

[0057] Using the slickwater fracturing fluid formulation applied in the field as the base fluid, the supernatant was obtained after gel breaking and filtration. Using a precision electronic balance (accuracy 0.0001g) and a pipette, stabilizers were added to the supernatant to prepare a series of clay stabilizer solutions with concentrations of 0%, 0.1%, 0.3%, 0.5%, 0.7%, and 1.0%, each in 1000mL. The solutions were then ultrasonically mixed to ensure homogeneity.

[0058] Step 3: Dynamic percolation experiment and NMR monitoring;

[0059] Rock samples were placed in the reaction chamber of a high-temperature, high-pressure permeabilizer (such as the American Temco HNP-100 model), and experimental conditions were set to simulate the actual formation environment: temperature: 60.0±0.5℃; confining pressure: 20.0±0.2 MPa; fluid salinity: 80000±200 mg / L (simulating formation water).

[0060] A series of clay stabilizer solutions were injected into the reaction chamber to ensure complete immersion of the rock samples. A low-field nuclear magnetic resonance (NMR) analyzer (such as the Suzhou Nuomai MesoMR23-060H-I model) was used to precisely acquire T2 spectral data of the rock samples at 0h, 2h, 6h, 12h, 24h, 48h, and 72h after the onset of percolation. The NMR analyzer parameters were set as follows: main frequency 23MHz, waiting time TW 3000ms, echo time TE 0.2ms, and number of scans NS 64.

[0061] Step 4: Calculation of the rate of change of liquid inflow K (taking a clay stabilizer solution concentration of 0.7% as an example):

[0062] A peak area of ​​nuclear magnetic resonance signal in rock sample before infiltration dry =3102.263, the peak area A of the NMR signal 2 hours after the start of osmosis. 2h =4076.663, the peak area A of the NMR signal 72 hours after the start of osmosis. 72h =7450.201;

[0063] Calculate K=[(A tmax -A dry )-(A tcritical -A dry )] / (A tmax -A dry= [(7450.201-3102.263)-(4076.663-3102.263)] / (7450.201-3102.263)=77.57%;

[0064] The change rate K of the influent volume for a series of clay stabilizer solutions was calculated sequentially, and the results are shown in Table 1.

[0065] Table 1 shows the calculation results of the change rate K of the influent volume for a series of clay stabilizer solutions.

[0066] .

[0067] Step 5: Calculation of the rate of change in permeability ΔK:

[0068] The calculation formula is: △K = |K0 - K i | / K0×100%; Calculate the permeability change rate ΔK corresponding to the series of clay stabilizer solutions in sequence. The calculation results are shown in Table 2.

[0069] Table 2 shows the calculation results of the permeability change rate ΔK for a series of clay stabilizer solutions.

[0070] ;

[0071] The degree of damage assessment is determined according to SY / T 5358-2010; the maximum penetration rate damage threshold △K is set according to the weak damage upper limit set in SY / T 5358-2010. max =30%.

[0072] Step 6: Calculate the first weighting coefficient α and the second weighting coefficient β;

[0073] The K-series of influent flow rate changes for the series of clay stabilizers are [41.48, 60.02, 62.36, 69.29, 77.57, 78.00], and their standard deviation σ is calculated. K ≈13.71, mean μ K =64.79, coefficient of variation (CV) of the rate of change in influent volume K K =σ K / μ K =13.71 / 64.79≈0.2115;

[0074] The permeability change rate ΔK sequence corresponding to the series of clay stabilizers is [39.32, 31.70, 35.39, 29.60, 21.45, 21.50]. The standard deviation σ is calculated. △K ≈7.19, mean μ △K =29.83, coefficient of variation (CV) of the rate of change in permeability ΔK △K =σ△K / μ △K =7.19 / 29.83≈0.2411;

[0075] The calculation yields α=CV K / (CV K +CV △K =0.2115 / (0.2115+0.2411)≈0.467, β≈0.533.

[0076] Step 7: Calculation of the Comprehensive Decision Index (CDI) (taking a clay stabilizer solution concentration of 0.7% as an example):

[0077] CDI = α(K / K0) + β(△K / △K) max =0.467×(77.57 / 41.48)+0.533×(21.45 / 30)=1.254;

[0078] The calculation results of the comprehensive decision index (CDI) corresponding to the series of clay stabilizer solutions are shown in Table 3;

[0079] Table 3 shows the calculation results of the Comprehensive Decision Index (CDI) for a series of clay stabilizer solutions.

[0080] ;

[0081] Based on the condition that the clay stabilizer concentration corresponding to the minimum value of the comprehensive decision index CDI is the optimal clay stabilizer concentration, 0.7% is determined to be the optimal clay stabilizer concentration.

[0082] Based on the above steps, the optimal concentrations of clay stabilizer solutions for fine sandstone, siltstone and mudstone were obtained, and the results are shown in Table 4 below.

[0083] Table 4. Summary of Optimization Results of Stabilizer Dosage for Different Lithotypes and Clay Types

[0084] ;

[0085] Therefore, the concentration of the clay stabilizer solution corresponding to fine sandstone is 0.3%, the concentration of the clay stabilizer solution corresponding to siltstone is 0.5%, and the concentration of the clay stabilizer solution corresponding to mudstone and shale is 0.7%.

Claims

1. A method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs, characterized in that, The method is as follows: Rock samples were subjected to percolation with clay stabilizer solutions of varying concentrations. The peak areas of the nuclear magnetic resonance (NMR) signals at different percolation times were obtained, leading to the acquisition of the percolation rate change (K-series) and permeability change (ΔK-series) for different concentration gradient clay stabilizer solutions. Based on the mean, standard deviation, and coefficient of variation of the percolation rate change (K-series) and permeability change (ΔK-series), the first weighting coefficient α and the second weighting coefficient β were obtained. Furthermore, the comprehensive decision index (CDI) sequence for different concentration gradient clay stabilizer solutions was calculated. The condition was that the permeability change rate (ΔK) ≤ the maximum permeability damage threshold (ΔK). max Furthermore, the concentration of the clay stabilizer solution corresponding to the minimum value of the comprehensive decision index CDI is the optimal clay stabilizer concentration; The specific solution process for the comprehensive decision index CDI is as follows: CDI = α(K / K0)+ β(△K / △K max ) Equation 1 In the formula: α is the first weighting coefficient; β is the second weighting coefficient; K is the rate of change of liquid inlet volume; K0 is the rate of change of liquid inlet volume when the concentration of clay stabilizer solution is 0. △K represents the rate of change in permeability; △K max This represents the maximum penetration damage threshold.

2. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 1, characterized in that, The specific solution process for the first weighting coefficient α and the second weighting coefficient β is as follows: α = CV K / (CV K + CV △K ) Equation 2 β = CV △K / (CV K + CV △K ) Equation 3 CV K =s K / m K formula 4 CV △K =s △K / m △K formula 5 Where: CV K σ is the coefficient of variation of the rate of change of the influent volume K; K μ K These are the standard deviation and mean of the rate of change of liquid inflow K, respectively; CV △K σ is the coefficient of variation of the rate of change in permeability ΔK; △K μ △K These are the standard deviation and mean of the permeability change rate ΔK, respectively.

3. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 1, characterized in that, The specific solution process for the rate of change of liquid inflow K is as follows: K=[(A tmax -THE dry )-(THE tcritical -THE dry )] / (THE tmax -THE dry ) formula 6 In the formula: A dry The peak area of ​​the nuclear magnetic resonance signal of the rock sample before infiltration; A tmax The peak area of ​​the NMR signal at the osmotic stability time point tmax; A tcritical The peak area of ​​the NMR signal at a specific time point tcritical during the initial stage of infiltration.

4. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 3, characterized in that, The different concentration gradients are specifically 0%, 0.1%, 0.3%, 0.5%, 0.7%, and 1.0%; the different absorption times are specifically 0h, 2h, 6h, 12h, 24h, 48h, and 72h.

5. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 4, characterized in that, The initial tcritical time point of the percolation is 2 hours after the start of percolation, and the stable tmax time point of percolation is 72 hours after the start of percolation.

6. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 1, characterized in that, The specific solution process for the permeability change rate ΔK is as follows: △K=|K0-K i | / K0 ×100% Formula 7 Where: K i This represents the permeability at a certain point in time after the start of osmosis.

7. The method for optimizing the dosage of clay stabilizer in low-permeability tight reservoirs according to claim 1, characterized in that, The maximum penetration damage threshold ΔK max It is 30%.

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