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Article

Exploring the Unique Characteristics of High-Pore-Volume Waterflooding and Enhanced Oil Recovery Mechanisms in Offshore Sandstone Reservoirs Using Nuclear Magnetic Resonance Technology

by
Junrong Liu
1,2,*,
Hangyu Li
1,2,*,
Jianchun Xu
1,2,
Shuyang Liu
1,2,
Rongjiang Liu
1,2,
Lianjie Hou
1,2 and
Qizhi Tan
1,2
1
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
2
Key Laboratory of Unconventional Oil & Gas Development, China University of Petroleum (East China), Qingdao 266580, China
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2023, 11(7), 1296; https://doi.org/10.3390/jmse11071296
Submission received: 30 May 2023 / Revised: 21 June 2023 / Accepted: 24 June 2023 / Published: 26 June 2023
(This article belongs to the Special Issue High-Efficient Exploration and Development of Oil & Gas from Ocean)
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Abstract

:

Simple Summary

The characteristics of high-pore-volume (high-PV) waterflooding and the mechanisms of enhanced oil recovery (EOR) are unclear. an experiment was conducted using nuclear magnetic resonance (NMR) technology-assisted waterflooding to monitor oil migration and pore structure changes during the displacement process. We quantified the ultimate oil displacement efficiency waterflooding and microscopic oil recovery at the pore scale. Additionally, the variations in petrophysical properties seen during this process were analyzed. The experiment revealed that the high-PV displacement process had a high EOR effect, even in the ultrahigh water cut stage. During this period, oil production came mainly from the mesopores. Furthermore, flooding changed the rock structure, increasing the pore volume. However, these changes were inconsistent at both the pore scale and spatial scale. At the pore scale, the volume of macropores decreased, while that of the micropores and mesopores increased. At the spatial scale, the porosity and the average pore size at the front end increased, while those at the back end decreased due to particle migration during flooding. Our findings suggested that pore structure variations at the front ends of experimental cores were representative of those in reservoirs, indicating that high-PV waterflooding could increase the permeabilities of reservoirs.

Abstract

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

1. Introduction

As the demand for oil continues to grow and onshore oilfields are gradually being depleted, offshore oil and gas resources have become important alternative energy sources [1,2,3,4]. Generally, utilizing natural waterflooding is a cost-effective and environmentally sustainable approach for enhancing oil recovery in offshore oilfields, with robust edge-bottom water energy [5,6,7,8,9]. To date, horizontal wells with large-volume water injection are the main development method for such offshore reservoirs, with oil recovery levels reaching 50%. Unlike conventional reservoirs, offshore reservoirs exhibit unique characteristics wherein the water cut increases swiftly after bottom water breakthrough, leading to an extended period of high water cut during the oil production stage.
During the high water cut stage, the characteristic curve of waterflooding differs from the traditional curve, which typically follows a semilogarithmic linear relationship between the oil–water relative permeability ratio (Kro/Krw) and the water saturation (Sw) value [10,11,12,13]. Numerous oilfield practices have indicated that the waterflooding characteristic curve tends to warp upward, even during the high water cut stage, suggesting that reservoirs possess significant production potential [7,14,15,16,17]. It has been reported that the XJ24-3 offshore oilfield has entered an ultrahigh water cut period, with oil recovery exceeding 60% since 2014. Despite this phenomenon, oil production has continued to increase steadily, as reported by Zhang et al. [16]. Tan et al. [7] found that oil recovery is still increasing by 22.2–34.2% at the high water cut stage (>98%) at the X oilfield in the Bohai Sea. In addition, the curve bends downward when the reservoir enters the ultrahigh water cut stage in indoor experiments [18,19]. Hence, the conventional seepage model cannot describe the oil production patterns of these reservoirs, especially regarding the high water cut stage with high multiple displacements.
In addition, it is difficult to predict the ultimate oil recovery of such oilfields via conventional experimental methods. According to the specification SY/T 5345—2007 [20], the final oil displacement efficiency is the extraction degree of the experimental core after 30 PV displacements or when the water cut is above 99.95%. For offshore reservoirs with strong edge-bottom waters, the displacement multiple is much greater than 30 PV, and considerable oil is still recovered after 30 PV of displacement. Zhang et al. [16] observed that the residual oil saturation decreases from 29.56% to 21.72% when the displacement multiple increases from 30 to 2000 PV, while high-PV water injection can further enhance oil recovery from the Xijiang oil field at the high water cut stage. Ji et al. [21] suggested that the residual oil saturation during the high water cut period is not constant; thus, the oil displacement efficiency measured by conventional core waterflooding experiments cannot represent the ultimate oil recovery rate of high-PV displacement reservoirs.
Thus far, several studies have indicated that wettability alteration and pore structure variation are two important EOR mechanisms of high-PV displacement waterflooding [22,23,24,25,26]. Xiong et al. [22] applied the contact angle to evaluate the wettability of rock during waterflooding and observed a shift in core wettability from oil–wet to intermediate–wet, which is beneficial for enhancing oil displacement efficiency [27,28,29,30,31]. In oil–wet systems, water tends to form continuous channels or ‘fingers’ through the centers of macropores, displacing oil ahead of the centers [32]. Consequently, oil becomes trapped in the small pores and ‘throats’. Conversely, in water–wet systems, the distribution of the two fluids is reversed, relative to the oil–wet system. Residual oil exists in the form of small, spherical globules in the centers of the large pores, and large patches of oil extend over multiple pores that are surrounded by water [29]. These studies suggest that wettability alteration leads to changes in the microscopic distribution of residual oil. To date, most research has focused on macroscopic core oil displacement efficiency, and there have been few studies on microscopic oil recovery at the pore scale.
Additionally, previous research has established that the pore structures of oil reservoirs are significantly changed during waterflooding due to the erosion and migration of mineral particles, resulting in variations in the petrophysical properties (e.g., porosity and permeability) that affect oil displacement efficiency [30,31,32,33,34,35,36]. In general, the permeability of a water-driven reservoir increases due to water washing. Li et al. [37] investigated the pore structure distribution during high-PV waterflooding in the Shuanghe Oilfield and found that the pore distribution range widens and many micropores and macropores are produced, while the effect of water injection is not obvious and is hard to predict. Although an increase in macropores is beneficial for increasing permeability, an increase in micropores may not necessarily have the same effect. Hence, the effects of pore structure changes induced by high-PV waterflooding on reservoir permeability are still unclear. Additionally, researchers usually use mercury injection tests to characterize pore structure changes before and after waterflooding. However, the mercury injection experiment is destructive; thus, researchers cannot repeat the waterflooding test using the same core sample. Because of the heterogeneity of the reservoir rock, the test results are not convincing enough.
Nuclear magnetic resonance (NMR), as a non-destructive and efficient method, can be utilized to address the above problems. The transverse relaxation (T2) spectrum, which is widely used in NMR, has been proposed as an effective approach for characterizing pore structures [37,38,39,40,41,42] and can be expressed as follows:
1 T 2 s u r f a c e = ρ 2 S V p o r e
where ρ2 represents the surface relaxivity associated with the transverse relaxation process, m/s; S V denotes the surface-to-volume ratio of the pore, 1/m.
In general, larger pores are associated with longer T2 values, while smaller pores tend to have shorter T2 values. However, the pore structure changes seen in different locations are heterogeneous. A new NMR method (the SE–SPI sequence) is applied to scan each layer of the experimental core to further understand the pore structure changes in various parts of the water-driven core.
Moreover, a dynamic T2 spectrum can accurately characterize oil distribution and oil migration among different pores [43,44,45]. Despite their potential benefits, few studies have investigated the impacts of high multiple displacements on microscopic oil displacement efficiency using NMR technology.
In this paper, we design an NMR technology-assisted waterflooding experiment to monitor oil migration and pore structure variations during the displacement process. The characteristics of high-PV waterflooding and the relevant EOR mechanisms are investigated. The results of this study provide a theoretical foundation and practical guidance for predicting performance and enhancing productivity in offshore sandstone reservoirs with high water cuts.

2. Methodology

An online NMR-monitored displacement experiment system was set up, as shown in Figure 1, to explore the micro EOR mechanisms and the time-varying law of petrophysical properties during high-PV waterflooding.
In the experiments, the simulated displacement multiples were greatly improved to accurately reflect the washout strengths of the actual reservoirs. Nuclear magnetic imaging (NMI) technology was utilized to image the sagittal planes of the experimental cores to capture the in situ changes in residual oil during the displacement process. Moreover, the CPMG (Carr–Purcell–Meiboom–Gill) sequence was used to obtain a dynamic T2 spectrum to quantify the oil displacement efficiency. This method has high test accuracy (1 mg of oil/water could be detected) and could avoid the errors seen in ordinary displacement experiments. Based on the corresponding relationship between relaxation time and pore size, the dynamic T2 spectrum could be used to analyze microscopic oil recovery at the pore scale. Furthermore, a SE–SPI sequence was applied to obtain a cross-section T2 spectrum by which to investigate the time-varying laws of petrophysical properties.

2.1. Characterization of Core and Fluid Properties

In this study, we obtained experimental cores from offshore sandstone reservoirs located in Bohai, China. These cores were prepared for waterflooding experiments by cutting into ϕ 25 × 50 mm cylinders. To track the migration of oil within the cores, we followed the processing procedure outlined in Figure 2 and employed NMR instruments. Sand filters were installed at both ends of the core to prevent particle movement from blocking the pipeline during waterflooding. Then, the experimental core was fixed with a nonmagnetic plug and a heat-shrink tube to meet the requirements of subsequent experiments. Prior to waterflooding, the experimental core was subjected to porosity and permeability measurements, which yielded values of 15.4% and 2385 mD, respectively.
To avoid the confounding influences of various factors, such as wettability alteration due to asphaltene adsorption, we utilized kerosene and diesel as the hydrocarbon phase instead of crude oil in this study. By selecting these two substances, we could isolate the effects of interest and gain a more accurate understanding of the oil migration behaviors under the specified conditions. The mixing ratio of the two oils was adjusted so that the viscosity of the experimental oil was close to that of crude oil under formation conditions (2.1 mPa·s). Additionally, the oil density was 0.83 g/cm3 at the experimental temperature.
For the waterflooding experiment, heavy water (D2O) was chosen as the displacing fluid due to its unique properties. Unlike ordinary water (H2O), heavy water does not generate NMR signals in a magnetic field. By using heavy water, the NMR signals from the water were eliminated, enabling the observation of oil migration within the pore space using the NMR instrument.

2.2. NMR-Monitored High-PV Waterflooding Experiments

To effectively monitor the movement of oil during waterflooding, we developed a high-PV waterflooding experimental system that utilized NMR technology, as illustrated in Figure 1. The experimental system comprises several essential components, including a piston pump, three accumulators, a core holder, an NMR instrument, a BPR (back pressure regulator) device, and two circulating pumps. The circulating pumps play a crucial role in maintaining the stability of the system temperature. It is worth highlighting that the core of this system features a low-field NMR instrument manufactured by the Niumag Corporation in China. By utilizing the MRI (magnetic resonance imaging) module of the instrument, we could visualize the residual oil and qualitatively assess the effectiveness of oil displacement during waterflooding. Furthermore, the dynamic T2 spectrum generated by inversion provided a quantitative analysis of microscopic displacement efficiency at the pore scale. The SE–SPI sequence was applied to characterize the pore distributions before and after high-PV waterflooding. Details of the experimental parameters for both modes are provided in Table 1.
The experimental protocol followed the industry standard, SY/T 5345—2007, except for an increased displacement multiple of 2000 PV. The specific steps involved in the experiment were as follows. (1) The experimental core was thoroughly cleaned using a toluene–ethanol solution and dried at a temperature of 105 ℃. The base NMR signal of the core was then measured. (2) The core was saturated with DI water (H2O), at an injection rate of 0.05 mL/min, and the resulting water-saturated core was tested using the NMR apparatus to acquire the whole and cross-sectional T2 spectra. (3) The core was saturated with oil at the same rate, to simulate the initial reservoir, and the NMR signal of the oil-saturated core in its initial state was recorded. (4) High-PV waterflooding experiments were conducted by injecting heavy water at the design speed (10 mL/min) and by recording NMR signals after the 0.5 PV, 1 PV, 30 PV, and 2000 PV waterflooding stages; (5) Following the 2000 PV stage, DI water was used to flood the core for an additional 10 PV to replace the heavy water. Finally, the NMR signals of the core were measured to characterize its pore structure after high-PV waterflooding.

3. Results and Discussion

3.1. Variations in Oil Displacement Efficiency

The NMR instrument captures sagittal images of the experimental cores during waterflooding, as illustrated in Figure 3. Since the NMR signals of the displacement fluid (heavy water) and rock skeleton are very weak, the images primarily reflect the amount of residual oil remaining in the core. The gradual reduction in the NMR signal during waterflooding indicates that this technique effectively reduces the residual oil saturation.
However, after 1 PV of waterflooding, the residual oil reduction is more significant at the injection end than at the exit end, suggesting spatial heterogeneity in the oil displacement effect. After 30 PV, the residual oil at the injection end is further reduced, but some large oil aggregates remain at the exit end due to microscopic heterogeneity. This heterogeneity is due to the presence of local areas with low permeability in the reservoir, which causes high seepage resistance of the crude oil and leads to the formation of microscopic heterogeneous residual oil.
As the waterflooding volume increases to 2000 PV, the residual oil greatly decreases, and the oil aggregates disappear, leaving sporadic dot-like residual oil inside the core. These MRI experimental results demonstrate that significant amounts of oil remain in the reservoirs even after conventional waterflooding (<30 PV) and that high-volume waterflooding can further enhance oil displacement efficiency.
To quantify the EOR effect of high-PV waterflooding, we recorded the dynamic T2 spectrum during the displacement process, as shown in Figure 4. Theoretically, the amount of hydrogen-containing fluid is proportional to its NMR signals (the envelope area of the T2 spectrum), based on the principles behind NMR technology.
To validate the instrument and confirm its ability to accurately reflect changes in oil volume within the cores, we measured the total NMR signals of cores saturated with varying volumes of oil, as illustrated in Figure 5. The results indicate a strong linear relationship between NMR signals and oil volume, confirming the effectiveness of the instrument and its ability to accurately reflect changes in oil volume within the cores. This finding enables us to derive the NMR signal–oil volume conversion relationship, as presented in Equation (2), and gain a better understanding of the oil migration process within the studied porous media:
V = 10 − 4 Q − 0.1133
where Q represents the total signal of NMR; V represents the oil volume in mL.
Then, the oil displacement efficiency can be calculated as follows:
R = V i − V r V i = 1 − V r V i = 1 − 10 − 4 Q r − 0.1133 10 − 4 Q i − 0.1133
where R represents the oil displacement efficiency; Vi represents the initial saturated oil volume in mL; Vr represents the residual oil volume in mL; Qi represents the total NMR signal of the initial state core; Qr represents the total NMR signal of the core after waterflooding.
Figure 6 illustrates how waterflooding affects oil displacement efficiency in reservoirs with varying PV values. Moreover, the water cut under different displacement multiples should be measured. In the process of waterflooding, the water cut increases rapidly and reaches 95.1% after water injection at 1 PV. This finding implies that the anhydrous oil production period is short and that the water cut increases rapidly after the water breakthrough. As the displacement multiple reaches 30 PV, the water cut grows to 99.5%, whereas the residual oil saturation is still as high as 33%; thus, the potential of EOR is very high. At the high-PV waterflooding stage (30–200 PV), the oil displacement efficiency increases from 67.0% to 83.7%, with a water cut of more than 99%. These experimental results indicate that the high-PV displacement process still has a good EOR effect at the ultrahigh water cut stage.

3.2. Microscopic Oil Displacement Efficiency at the Pore Scale

To further investigate the microscopic EOR mechanisms of high-PV waterflooding, we calculated the oil displacement efficiencies in different pores using dynamic T2 spectra. This spectrum not only characterizes the oil content of the rock but also reflects the distribution of oil in the pores. To quantify the correspondence between pore size and T2 relaxation time, the T2 spectrum (initial oil-saturated core) and mercury injection results were integrated, as demonstrated in Figure 7. We then selected the corresponding peak points (marked with green and black circles) of the two curves to calculate the conversion coefficient with Equation (4) [46]:
T 2 = C r
where T2 is the relaxation time in ms; C is the constant conversion coefficient in ms/μm; and r is the pore radius in μm.
We obtained very similar coefficients of 0.38 and 0.39 from our calculations, indicating a strong correspondence between the T2 relaxation time and pore radius. The average coefficient, 0.385, was utilized in this experiment. Consequently, the dynamic T2 spectrum illustrated in Figure 4 was used to characterize the microscopic oil displacement efficiencies of pores with varying radii.
Subsequently, we classified the pore types based on their T2 values, with the peak points being used as the cutoff values to divide the spectra, as described by Dai et al. [47]. Specifically, we classified the pores corresponding to T2 values ranging from 0–2.3 ms, 2.3–62.4 ms, and 62.4–10,000 ms as micropores, mesopores, and macropores, respectively, as presented in Table 2.
The microscopic oil displacement efficiencies in different types of pores can be quantified as follows:
R x = 1 − V r x V i x = 1 − 10 − 4 Q r x − 0.1133 10 − 4 Q i x − 0.1133
where Rx is the oil displacement efficiency of x-type pores; x refers to different pore types (micropore, mesopore, and macropore); Vrx is the residual oil volume in x-type pores, measured in mL; Vix is the initial oil-saturated volume in x-type pores, measured in mL; Qix is the total NMR signal in the relaxation interval to which the initial x-type pores belong. Qxr is the total NMR signal in the relaxation interval of the x-type pores after waterflooding.
Figure 8 shows the microscopic oil displacement efficiencies in different pore types after various displacement multiples. Due to the greater capillary resistance found in smaller pores, the displacement of stored oil by waterflooding becomes increasingly difficult. As a result, after waterflooding at 1 PV, the oil displacement efficiencies of micropores, mesopores, and macropores are roughly equivalent. During conventional low-multiple waterflooding (1–30 PV), the oil displacement efficiencies in mesopores and macropores increase by 11.8% and 23.1%, respectively, while the increase in micropores is only 1%. However, the residual oil saturation levels in micropores and mesopores remain high, at 41.9% and 38.7%, respectively.
In the high-PV waterflooding stage (30–2000 PV), the oil displacement efficiencies in micropores and mesopores increased by 17.2% and 24.7%, respectively, while the improvement in macropores was 4.6%. The washing action of high-PV waterflooding can alter the wettability of the oil–wet rock surface, enabling the displacement of the oil trapped in micropores or mesopores by capillary force. As most of the oil in macropores is displaced during the low-multiple waterflooding stage (<30 PV), the oil displacement efficiencies in macropores do not improve noticeably during high-PV waterflooding.
In addition, the proportion of oil production from different types of pores during high-PV (30–2000 PV) waterflooding is demonstrated in Figure 9. The results suggest that mesopores are the primary contributors to oil production, accounting for 70.7% of the total production. Although the oil displacement efficiencies in micropores improve significantly, contributing to 14.6% of total production, their contribution is not outstanding due to the tight oil storage space.

3.3. Time-Varying Petrophysical Properties of High Multiple Waterflooding Cores

3.3.1. Pore Structure Variation

The T2 spectra of the core that was fully saturated with DI water before and after flooding are presented in Figure 10A. Notably, after heavy waterflooding, the core shows almost no NMR signal. To characterize the pore structure after waterflooding, we injected 10 PV of DI water to displace the heavy water. The relationship between the total NMR signal and the saturated DI water volume is measured and plotted in Figure 10B. The volume of saturated water is equal to the pore volume of the experimental core. Therefore, we calculated the porosities before and after waterflooding to be 15.4% and 17.9%, respectively. This finding indicates that high-PV waterflooding changes the rock structure and increases the rock pore volume.
To investigate the increments in different types of pores, we applied the pore classification method described in Section 3.2 and plotted the results as shown in Figure 11. The volumes of the mesopores and micropores increased by 0.59 mL and 0.32 mL, respectively, while that of the macropores decreased by 0.47 mL. Although the overall porosity of rock increased after high-PV waterflooding, the changes in the different types of pores were not consistent. Among the pore types, the porosity of the mesopores increased the most, whereas that of the macropores decreased.
To further understand the pore structure variations at different locations of the experimental core, we applied the NMR tomography method to scan each layer, as shown in Figure 12. By comparing the cross-section T2 spectrum along the water-driving direction before and after waterflooding, we observed different pore structure changes at the front and back of the core. The peak value of the front T2 spectrum shifted to the right, indicating that the mean pore size increased, whereas the peak value of the back T2 spectrum shifted to the left, indicating that the mean pore size decreased.
Moreover, we quantified the pore structure variations in the different sections using a similar method to that in Section 3.2, as shown in Figure 13. The pore volumes of each section at the front increased to different degrees, while those at the back section decreased. Recent evidence suggests that the pore structure variation seen during high-PV waterflooding is mainly caused by the particle migration induced by the flushing action of the displacement fluid. Near the injection end, loose rock particles peel off and migrate, increasing the pore volume. As the outlet widens, the flow rate slows, resulting in the accumulation and migration of particles at the outlet, and the pore volume decreases accordingly.
Furthermore, the changes in the different types of pores before and after waterflooding in layers 1 (injection end) and 7 (outlet end) were compared, as shown in Figure 14. In layer 1, the volumes of mesopores and macropores increased by 0.17 mL and 0.01 mL, respectively, while the micropores were basically eliminated. This phenomenon can be attributed to the stripping of particles within a micropore to form a mesopore or macropore, increasing the average pore size at the front end. In contrast, in layer 7, the volume of mesopores decreased sharply by 0.27 mL, while the volume of micropores increased by 0.08 mL, and the volume of macropores remained relatively stable. This result suggests that the migrated particles mainly accumulate in the mesopores, transforming them into micropores, and decreasing the average pore size at the back end. The experimental results reveal that the pore structure variation induced by high-PV waterflooding is inconsistent at the microscale and at the spatial scale.

3.3.2. Permeability Variation

To further analyze the impact of high-PV waterflooding on the reservoir, it is essential to investigate the corresponding permeability variation. The change in pore structure induced by high-PV waterflooding inevitably leads to permeability variation. As the displacement process progresses, the water cut exceeds 95%, and the instantaneous oil/water saturation change is minimal, indicating that the high-PV waterflooding process is a steady-state process. Hence, the water relative permeability can be calculated using Darcy’s formula (shown in Equation (6)) by monitoring the pressure change at the injection end during the displacement process, as depicted in Figure 15:
K r w = Q w μ w L A Δ P
where Krw is the water relative permeability, measured in mD; Qw is the water flux, measured in cm3/s; μw is the viscosity of water, measured in mPa·s; L is the length of the experimental core in cm; A is the cross-section area of the experimental core in cm2; ΔP is the pressure difference between the two ends of the core, measured in 10−1 MPa.
The findings indicate that increasing the displacement multiple decreases water relative permeability. This phenomenon is contradictory to the theoretical prediction that increasing water saturation and porosity increases the water relative permeability [48,49,50]. This contradiction can be attributed to the inconsistency of rock structure variations, on both the pore scale and the spatial scale. Although the overall porosity of rock increases, at the pore scale, the volume of macropores decreases, while that of micropores and mesopores increases. At the spatial scale, the pore volume at the front increases while that at the back decreases, and the average pore size at the front increases while that at the back decreases. Thus, the permeability at the front increases, while that at the back decreases. The experimental core can be considered to be a series of small cores (scanning layers), and the overall permeability can be calculated as follows:
K = ∑ i = 1 n L i ∑ i = 1 n L i K i
where K represents the overall permeability of the experimental core, measured in mD; i refers to the scanning layers; n refers to the number of scanning layers; Li represents the length of the i-layer core in cm; and Ki represents the permeability of the i-layer core, measured in mD. According to Equation (7), the overall permeability of the experimental core is governed by the layer with the lowest permeability. According to the experimental results, the particle accumulation at the outlet of the core caused a sharp reduction in the permeability of the entire core. The increase in micropores and the decrease in mesopores seen in layer 7 due to the migration of fine particles decreased the average pore size at the back end, thereby contributing to the permeability reduction. This finding underscores the crucial role of pore structure variations induced by high-PV waterflooding in determining the overall permeability of the rock core.
Notably, particle accumulation at the end of the experimental core during waterflooding may not necessarily occur in actual reservoirs. As shown in Figure 16, reservoirs lack filters that prevent rock particle migration and the capillary end effect, which promotes particle deposition at the outlet of the core samples. Consequently, the pore structure variation at the front of the experimental cores may better reflect the actual changes caused by high-PV waterflooding; the permeability of reservoirs after such flooding is likely to increase, which contrasts with the experimental results. Further studies are needed to explore methods for accurately detecting the change in permeability during high-PV waterflooding in real reservoirs.

4. Conclusions

In this study, we present a new NMR-monitored displacement experimental method for investigating microscale EOR mechanisms and time-varying petrophysical properties during high-PV waterflooding. The main findings can be summarized as follows:
(1)
Conventional waterflooding (≤30 PV) results in brief oil production without the presence of water. However, it is followed by a swift rise in the water cut reach of up to 99%, while the residual oil saturation is still as high as 33%.
(2)
The high-PV displacement process shows a high EOR effect even in the ultrahigh water cut stage, resulting in a notable increase in the recovery rate by 16.7%. Notably, a significant portion of oil production, amounting to 70.7% of the total, primarily originates from the mesopores.
(3)
High-PV waterflooding induces changes in the rock structure, increasing porosity. However, the structure variation exhibits inconsistency at the pore scale with a decreased volume of macropores and increased volumes of micropores and mesopores.
(4)
The pore structure variation during high-PV waterflooding shows heterogeneity in the spatial scale, with increased pore volume at the front and decreased pore volume at the back. These changes in pore structure are the main reasons for the decline in rock permeability.
(5)
The changes in permeability obtained in the core experiment may not reflect those in reservoirs since particle accumulation at the end of the core during waterflooding may not occur in actual reservoirs. The pore structure variation at the front of the experimental cores may truly reflect that found in reservoirs, indicating that the permeability of reservoirs after high-PV waterflooding is likely to be increased.
Overall, the results of this study provide valuable insights into high-PV waterflooding and highlight the need for further research on methods for detecting changes in permeability during the high-PV waterflooding processes of real reservoirs.

Author Contributions

Conceptualization, Methodology, Investigation, Formal analysis, Writing—original draft, Writing—review & editing, J.L.; Supervision, Funding acquisition, Project administration, Writing—review & editing, H.L.; Conceptualization, Supervision, J.X.; Methodology, Investigation, Validation, S.L.; Methodology, Investigation, R.L.; Methodology, Investigation, L.H.; Writing—review & editing, Q.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shandong Provincial Natural Science Foundation, China (No. ZR2021JQ18) and the National Natural Science Foundation of China (No. 52074337 and No. 52204065, and No. 51904323).

Institutional Review Board Statement

The study did not require ethical approval.

Informed Consent Statement

The study did not involve humans.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Nuclear magnetic resonance (NMR) technology-assisted experimental system to evaluate waterflooding.
Figure 1. Nuclear magnetic resonance (NMR) technology-assisted experimental system to evaluate waterflooding.
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Figure 2. Experimental core treatment.
Figure 2. Experimental core treatment.
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Figure 3. Sagittal images of experimental cores during waterflooding.
Figure 3. Sagittal images of experimental cores during waterflooding.
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Figure 4. Dynamic T2 spectrum of the core during waterflooding.
Figure 4. Dynamic T2 spectrum of the core during waterflooding.
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Figure 5. Relationship between the total NMR signals and experimental oil volume.
Figure 5. Relationship between the total NMR signals and experimental oil volume.
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Figure 6. Oil displacement efficiency and water cut values under different displacement multiples.
Figure 6. Oil displacement efficiency and water cut values under different displacement multiples.
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Figure 7. Pore size distribution in the experimental core (NMR and mercury injection test).
Figure 7. Pore size distribution in the experimental core (NMR and mercury injection test).
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Figure 8. Oil displacement efficiency in different types of pores during waterflooding.
Figure 8. Oil displacement efficiency in different types of pores during waterflooding.
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Figure 9. Contributions of the different types of pores to oil production during high-PV (30–2000 PV) waterflooding.
Figure 9. Contributions of the different types of pores to oil production during high-PV (30–2000 PV) waterflooding.
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Figure 10. T2 spectrum of the DI water-saturated core before and after waterflooding (A). Relationship between the total NMR signal and saturated DI water volume (B).
Figure 10. T2 spectrum of the DI water-saturated core before and after waterflooding (A). Relationship between the total NMR signal and saturated DI water volume (B).
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Figure 11. Volumes of the various pores before and after high-PV waterflooding.
Figure 11. Volumes of the various pores before and after high-PV waterflooding.
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Figure 12. Cross-section T2 spectrum along the water-driving direction before waterflooding (A) and after 2000 PV waterflooding (B).
Figure 12. Cross-section T2 spectrum along the water-driving direction before waterflooding (A) and after 2000 PV waterflooding (B).
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Figure 13. Pore volumes of the different scanning layers before and after waterflooding.
Figure 13. Pore volumes of the different scanning layers before and after waterflooding.
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Figure 14. Pore volume variations in the different scanning layers before and after waterflooding.
Figure 14. Pore volume variations in the different scanning layers before and after waterflooding.
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Figure 15. Variations in water relative permeability during waterflooding.
Figure 15. Variations in water relative permeability during waterflooding.
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Figure 16. Comparison of the waterflooding process at reservoir scale and laboratory scale.
Figure 16. Comparison of the waterflooding process at reservoir scale and laboratory scale.
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Table
Table 1. Key parameters of the NMR instruments.
Table 1. Key parameters of the NMR instruments.
FunctionPulse SequencesField Strength (MHz)Gradient Strength
(T/m)		TW
(ms)		TE
(ms)		Scanning TimesTemperature (°C)
T2CPMG12010000.16432
cross-section T2SE-SPI120.048710000.16432
TW: waiting times; TE: echo spacings.
Table
Table 2. Pore size classification.
Table 2. Pore size classification.
T2 Relaxation Time, msPore Radius (R), μmPore Type
T2 ≤ 2.3R ≤ 6.0Micropore
2.3 < T2 ≤ 62.46.0 < R ≤ 162.1 Mesopore
T2 > 62.4R > 162.1 Macropore
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Liu, J.; Li, H.; Xu, J.; Liu, S.; Liu, R.; Hou, L.; Tan, Q. Exploring the Unique Characteristics of High-Pore-Volume Waterflooding and Enhanced Oil Recovery Mechanisms in Offshore Sandstone Reservoirs Using Nuclear Magnetic Resonance Technology. J. Mar. Sci. Eng. 2023, 11, 1296. https://doi.org/10.3390/jmse11071296

AMA Style

Liu J, Li H, Xu J, Liu S, Liu R, Hou L, Tan Q. Exploring the Unique Characteristics of High-Pore-Volume Waterflooding and Enhanced Oil Recovery Mechanisms in Offshore Sandstone Reservoirs Using Nuclear Magnetic Resonance Technology. Journal of Marine Science and Engineering. 2023; 11(7):1296. https://doi.org/10.3390/jmse11071296

Chicago/Turabian Style

Liu, Junrong, Hangyu Li, Jianchun Xu, Shuyang Liu, Rongjiang Liu, Lianjie Hou, and Qizhi Tan. 2023. "Exploring the Unique Characteristics of High-Pore-Volume Waterflooding and Enhanced Oil Recovery Mechanisms in Offshore Sandstone Reservoirs Using Nuclear Magnetic Resonance Technology" Journal of Marine Science and Engineering 11, no. 7: 1296. https://doi.org/10.3390/jmse11071296

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