Volcanic rock reservoir is one of the key exploration targets in the Changling fault depression of the Songliao Basin in recent years. The logging responses of complex volcanic lithologies are crucial to clarifying the reservoir properties (lithology, physical property, electrical property, and oil-bearing property). Based on the microscopic analysis of complex volcanic lithology, the lithology of volcanic rocks in the Huoshiling formation of the Chaganhua subsag in the Changling fault depression was calibrated through thin-section examination, whole-rock X-ray diffraction (XRD) analysis, and quantitative analysis using the RoqScan mineral auto-identification system. The conventional logging data and elemental logging data of the calibrated interval were divided into training set and test set. The training set was used to fit the target lithology, and the test set was loaded into the model calculation for prediction. Moreover, the model was employed in blind well testing. The results show that the volcanic rocks in the Huoshiling formation of the Chaganhua subsag in the Changling fault depression can be categorized into 5 classes such as volcanic lava, pyroclastic lava, pyroclastic rock, sedimentary pyroclastic rock, and pyroclastic sedimentary rock, indicating complex and varying lithologies. Six algorithms, i.e. decision tree, LightGBM, random forest, neural network, K-nearest neighbor (KNN), and extra-trees classifier (ETC), were compared for distinguishing lithology, revealing the accuracy of above 77% for all algorithms. ETC exhibits the best performance, with an accuracy up to 90%. This model has a strong generalization ability and yields an accuracy of 89% in blind well testing while correcting the results of original cutting logging. It can accurately identify and predict the lithology of volcanic rocks in the study area and provide intelligent support for subsequent volcanic oil and gas exploration and development.
Steam stimulation in horizontal wells in heavy oil reservoirs fails to achieve uniform exploitation and precise potential tapping via horizontal section. Conventional methods mostly consider the horizontal section as a whole, but overlook unbalanced producing due to reservoir heterogeneity, leading to vague understanding of remaining oil distribution and indefinite direction of potential tapping. This paper presents a segmented method of calculating drainage radius of a horizontal well. This method employs acoustic time difference (AC) to characterize reservoir heterogeneity, with the difference between adjacent AC averages >15% as a threshold to segment horizontal section. Depending on the relationship among single-well recovery efficiency, sweep efficiency, and displacement efficiency, a drainage radius calculation model is constructed to determine segment-specific drainage radius, quantitatively characterize drainage area, and accurately map remaining oil distribution zones. The application of this model in the heavy oil reservoir in the Chun 10 block of Chunguang oilfield reveals that the reservoir in the block is highly heterogeneous, where the segments of horizontal section divided by AC are greatly varying in drainage radius - from 5 to 110 m in individual wells, and the recovery is extremely disproportionate along the horizontal section. Guided by remaining oil distribution patterns, target orientations are optimized, and accordingly infill wells are accurately placed to effectively avoid the drainage interference from existing wells, thereby achieving enhanced development effects. This study provides a new method for calculating drainage radius of horizontal well in heterogeneous reservoirs, which enables a simple and rapid determination of single-well drainage radius, offering a technical support for further development of heavy oil reservoirs after steam stimulation.
Current research on reservoir flow units often neglects the flow unit transformation caused by development engineering factors, resulting in flow unit classification that do not match the actual development status of oilfields. To provide a flow unit classification more in line with the distribution of artificial fractures after perforation and fracturing, this paper takes the Chang 8 tight oil reservoir in the Fuxian area of the Ordos Basin as an example for investigation. Based on selected parameters (5 static parameters and 2 dynamic parameters), the Chang 8 tight oil reservoir was categorized into 4 classes of original flow units and developed flow units through cluster analysis. Combining discriminant analysis with microscopic pore structure, the classification was verified. Finally, the distribution of original and developed flow units was characterized, and the application of the flow units to reservoir development was clarified. The results show that original flow units are controlled by sedimentary microfacies, while developed flow units are controlled by engineering factors such as perforation thickness, proppant injection intensity, and water injection rate. After reservoir fracturing, the remaining oil zone gradually shifts towards lower-level flow units. Class A and B developed flow units should be developed by controlling injection pressure and optimizing perforation horizons. Re-fracturing or augmented injection should be conducted to improve development efficiency for Class C and D developed flow units.
Microsphere flooding technology can effectively address the issues of severe water channeling in high-permeability layers and difficult oil mobilizing in low-permeability layers in low-permeability reservoirs. This paper investigates the microscopic retention and plugging characteristics of microspheres by combining a parallel dual-core microsphere flooding physical simulation experiment with low-field nuclear magnetic resonance (NMR) testing, and quantitatively evaluates the microscopic plugging capacity of microspheres by defining the degree of core plugging and the plugging contributions of large and small pores. The results show that microsphere flooding can further enhance oil recovery. Microsphere injection at varying rates after water flooding enables the oil recovery of low-permeability and high-permeability cores to increase by an average of 9.47% and 5.80%, respectively. The permeabilities of the cores reduce to a varying extent after microsphere flooding, with a higher reduction in low-permeability cores than in high-permeability cores. The NMR test results indicate that the plugging degree of microspheres in low-permeability cores is greater than that in high-permeability cores. The average plugging degrees of low-permeability and high-permeability cores at different injection rates are 5.44% and 1.02%, respectively, suggesting that microspheres with a diameter of 50 nm used in the test are compatible with low-permeability cores. Additionally, the calculation results show that the plugging contribution rate of large pores is higher than that of small pores, with the latter being negative, indicating that microspheres preferentially deposit in large pores and displace the water in large pores into small pores, thereby mobilizing the fluocarbon oil in small pores.
For edge-water heavy oil reservoirs, the critical edge-water distance during steam huff and puff is vital for the placement of new wells and the development adjustment of existing wells. When a well for steam huff and puff is placed at a distance less than the critical edge-water distance, edge-water invasion may easily occur, resulting in poor development effect of heavy oil reservoirs. In this paper, the formation after steam huff and puff is divided into a thermally swept zone and a cold zone, and a characterization method of flow field parameters after steam huff and puff is determined. The comprehensive mobility of the thermally swept zone is equivalent to the comprehensive mobility of the cold zone by transforming the length of the thermally swept zone. On this basis, the calculation method of critical edge-water distance during steam huff and puff in heavy oil reservoirs is established considering the start-up pressure gradient of heavy oil, together with the mirror reflection and the potential superposition theory. The results show that the relationship curve between the critical edge-water distance and the permeability is plotted to guide the placement of new wells, effectively preventing edge-water invasion, and the relationship curve between the cumulative liquid production and the cumulative steam injection volume under different edge-water distances is provided to support the optimization of the cyclic steam injection volume in existing wells. Field application in Well A demonstrated that the critical edge-water distance was reduced from 180 m in the first cycle to 150 m in the second cycle, effectively preventing edge-water invasion. By optimizing the cyclic steam injection volume, the steam huff and puff recovery has been increased by 3.1%.
The complex and highly heterogeneous reservoir space in the Ordovician carbonate reservoirs in Tahe oilfield poses significant challenges to reservoir characterization and modeling. This paper proposes a modeling method for fault-controlled reservoirs based on internal filling model, enabling the construction of a high-precision model with the methodology of lithology-structure dual constraints, hierarchical modeling, and categorical integration. First, depending on the genesis of fault-controlled reservoirs and the characteristics of reservoir architectures, the reservoirs are divided into three types of structural units: vugs, pores, and fractures. Vugs and pores are delineated by using deterministic modelling with cutoff value and corrected manually to define their boundaries; combined with log-derived lithofacies, the reservoirs are identified, and the internal architecture is finely characterized by integrating deep neural network with seismic inversion data. Faults and fractures are characterized at different scales: large faults are identified through ant-tracking and coherence attributes; small-medium faults are defined by diffraction tensor ant-tracking with volume constraints; and fractures are finely described via discrete fracture network (DFN) modeling. Next, based on the coupling of genetic mechanism, storage-permeability function, and engineering application, multi-scale model integration is performed. Finally, a matrix-fracture dual-medium geological model is established. Application in a unit of the Tahe oilfield has demonstrated that the high-precision filling model yields the validated results of static reserves and production performance in good agreement with the actual production data. The proposed model can effectively support the simulations of remaining oil recovery and development adjustment, and significantly enhance the reliability of numerical simulation for such reservoirs.
Nuclear magnetic resonance (NMR) logging is a critical method for obtaining the porosity of shale oil reservoirs, but the varying vertical resolutions of different logging tools severely affect the division of oil layer thickness and the characterization of sweet spots. The spectral characteristics of different NMR effective porosity curves were analyzed through the Fourier transform. With the spectral amplitudes of the logs including microspherically focused resistivity, acoustic, neutron porosity, and P-type NMR effective porosities selected using the ReliefF algorithm as the input features for the machine learning (ML) model, and the spectral amplitude of CMR-type NMR effective porosity log as the target value, a prediction model for the spectral amplitude of NMR effective porosity was constructed using decision tree (DT) and LSBoost ensemble tree. The prediction results of different ML models were compared, showing that the LSBoost ensemble tree model is the most accurate. For purpose of resolution matching among different NMR logs, the time-frequency analysis was innovatively integrated with the resolution matching to form a method for improving the resolution of NMR effective porosity log through spectral amplitude transplantation. This method has been validated to significantly enhance the resolution of low-resolution NMR effective porosity logs. The reconstructed NMR effective porosity logs are significantly superior in oil layer thickness division, fully proving that this resolution matching method is highly promising, laying a foundation for the precise characterization of sweet spot distribution and the efficient extraction of shale oil in the Permian Luocaogou formation in the Jimsar sag of the Junggar Basin. However, this method is limited when applied in strata with high pyrite content or small thickness.
Deep seismic signals exhibit serious high-frequency energy attenuation, leading to lower resolution than required level in production. Conventional frequency-increasing methods primarily operate on the amplitude spectrum of seismic signals, but cannot restore original phase spectrum, resulting in signal distortion and poor lateral continuity of events. Based on the time-frequency analysis of S transform, this paper proposes a method that directly performs spectral whitening on point complex spectrum to ensure that the phase of seismic signals remains unchanged before and after point complex spectral operation, which can effectively improve seismic data resolution while preserving signal-to-noise ratio and lateral continuity of seismic events. The conventional deconvolution method, traditional spectral whitening frequency-increasing method and point complex spectrum-based frequency-increasing method were applied to the seismic data processing of the Permian Lucaogou formation in the Jimsar sag. It is found that the point complex spectrum-based frequency-increasing method is better performed than the other two methods, and it can provide high-fidelity, amplitude-preserving, high-resolution seismic data for seismic prediction of thin sweet spots.
Based on the high-precision petrophysical experiments and the data acquired by new logging techniques, a logging-based characterization was conducted on three key parameters (lithofacies, effective porosity, and movable oil porosity) of shale oil reservoirs in the Fengcheng formation of Mahu sag, Junggar Basin. The following results are obtained. First, according to the core characteristics, FMI images, pore types, and mineral contents, the Fengcheng shale oil reservoirs are divided into felsic, dolomitic/calcareous, and clayey mixed lithofacies. The diamictite index and micro-pore index are constructed to identify lithofacies. Second, a tight reservoir analysis (TRA) experiment is performed to measure porosity of rock samples, confirming that the felsic lithofacies presents the best physical properties. Using TRA experiment results to calibrate the NMR logging data, an effective porosity characterization model with variable T2 cutoff of different lithofacies is established. Third, through comparison of multi-state T1-T2 NMR experiments, and considering the NMR logging responses, the positions of movable oil, bound oil, capillary bound water, asphalt and clay bound water of three lithofacies are revealed, and the shale oil occurrence identification chart is formed. According to the characterization results of lithofacies, effective porosity and movable oil porosity, together with the fluid production profiles of key wells, it is clarified that the interbedding of felsic lithofacies and clayey mixed lithofacies forms a favorable lithofacies combination in the Fengcheng formation. The research provides technical support for the experimental analysis of other continental shale oil reservoirs in China, and contributes a reference for shale oil reservoir evaluation.
Horizontal wells are widely used in the development of shale oil reservoirs. Due to the presence of thin interlayers in and significant anisotropy of the reservoir, there is an obvious difference between the acoustic slowness measured in horizontal wells and that measured in vertical wells, which seriously affects the interpretation accuracy of horizontal wells. In this paper, the four-component rotation technique is applied to process dipole array acoustic data for correcting shear-wave anisotropy. The slow shear-wave slowness obtained by this method is difficult to be accurately extracted due to serious dispersion effect. To solve this problem, a functional relationship between shear-wave anisotropy ratio and clay mineral content is established through analyzing horizontal well logging data of typical shale oil reservoirs in different basins, and a transformation relationship between the anisotropy ratios of compressional wave and shear wave is defined by using the core experimental data of these reservoirs. In practical processing, the anisotropy ratios of compressional- and shear-waves are obtained based on the clay mineral content. By combining the fast compressional-wave and shear-wave slowness values extracted from the acoustic logging data, the measured acoustic anisotropy of horizontal well is corrected. This correction method has been used to the actual horizontal well measurements in different basins, suggesting that the corrected acoustic slowness well agrees with the measured value of adjacent vertical well. The porosity calculated by the corrected acoustic slowness is basically consistent with the porosity calculated from the density logging. The results indicate that the proposed correction method is effective, and the corrected acoustic slowness can be used for calculating reservoir and engineering evaluation parameters for shale oil.
Offshore low-permeability reservoirs are characterized by fine lithology, poor physical property, and strong heterogeneity, making permeability prediction highly challenging. To address this issue, a regression committee learning machine (RCLM) driven by both data and physics was developed for predicting permeability based on logging data for low-permeability reservoirs. On this basis, sweet spot evaluation and dynamic permeability prediction were conducted. The results show that compared with a simple learning machine, the RCLM not only guarantees the prediction accuracy but also achieves higher prediction stability; in comparison with conventional porosity-permeability models, the RCLM obtains superior accuracy (up to 94% within half an order of magnitude). The comprehensive logging-based sweet spot index established using logging curves and petrophysical parameters can be used to effectively identify sweet spots in reservoirs. The newly drilled wells have verified the applicability of the dynamic-static permeability transformation model, which can be used to predict well test-derived permeability during regionally progressive exploration and development. The proposed method has been successfully applied in reservoir evaluation in the Dongfang gas field of the Yinggehai Basin, demonstrating its practical value. This method may provide robust support for efficiently designing exploration and development plan for offshore gas fields.
Accurate evaluation of performance decline is crucial for efficient development of gas fields and ensuring stable energy supply. Production decline rate and productivity decline rate are two commonly used parameters for presenting performance decline in gas fields from different perspectives, but their definitions are different. In order to understand the physical meanings of production decline rate and productivity decline rate and clarify their inherent relationship and influencing factors, the calculation method of gas field decline rate was analyzed, and the influencing factors were identified. The results indicate that, for exponential decline, the productivity decline rate are consistent with the production decline rate, while for hyperbolic decline, the productivity decline rate is always greater than the production decline rate, and the difference between the two decline rates increases with the increase of decline index and initial decline rate, and the two rates gradually tend to be consistent with each other with the extension of production time. The concept of gas field exploitation intensity was introduced to eliminate the fluctuations in production decline rate caused by downstream gas consumption changes. A new method of production/productivity prediction was proposed. Specifically, an exponential decline model is used at the early stage of decline, and a harmonic decline model is used at the mid to late stage of decline; then, the average of the two model results is taken as the lower limit, and the result obtained from the harmonic decline model as the upper limit. The research results are of great significance to accurately analyze the decline behaviors of gas fields and scientifically formulate development plans.
The CO2 storage and enhanced gas recovery (CS-EGR) technology represents a promising option for boosting production in the context of “dual carbon” goals. However, its application in tight sandstone gas reservoirs has been scarcely studied, and its field performance remains unclear. This study establishes a reservoir-scale numerical model based on a comprehensive analysis of gas-water two-phase flow mechanisms and stress sensitivity across three reservoir types. Using this model, the adaptability of CO2 injection to reservoirs, CO2 migration behaviors, CO2 trapping mechanisms, impacts of movable water on the CS-EGR process, and optimization of engineering parameters for CS-EGR are analyzed. It is indicated that CS-EGR is viable only for Class Ⅰ reservoirs, but less performed in Class Ⅱ and Class Ⅲ reservoirs. In terms of CO2 trapping mechanism, both structural trapping and residual trapping account for 95.8%, while CO2 mineralization and storage contributes 0.15%. For Class Ⅰ reservoirs, the optimal CO2 injection rate is 10,000 m3/d, the cumulative production of CH4 is 0.146×108 m3 when CO2 breaking through, and the cumulative storage of CO2 is 0.794×108 m3. Movable water significantly hinders CO2 migration and increases the risk of gas well flooding.
Flue gas-assisted steam flooding is an economically viable enhanced oil recovery (EOR) technology for heavy oil reservoirs. To address the complex mechanisms of synergy between flue gas injection and steam injection, and the unclear impacts of injection process and reservoir properties on development performance, experiments and numerical simulations were performed on flue gas-assisted steam flooding following conventional steam flooding. Taking a heavy oil reservoir as an example, core flooding experiments were conducted to compare oil displacement efficiencies under different injection media. A mechanistic model of flue gas-assisted steam flooding for heavy oil reservoirs was established to systematically investigate its underlying mechanism and performance. The research results show that flue gas-assisted steam flooding improves oil recovery efficiency by 5.84% compared to pure steam flooding, attributed to multiple mechanisms such as thermal viscosity reduction by steam, pressurization effect of flue gas, enhanced thermal sweep efficiency via gis-liquid Jamin effect, and oil mobilization by flue gas flow. The injected flue gas forms a gas zone at the steam chamber front, prolonging steam-oil interaction time while mitigating steam override, thereby expanding thermal sweep area. An optimal steam-to-flue gas molar ratio of 7∶3 during injection can achieve a favorable balance between enhanced oil recovery and reduced steam consumption. Slug injection generates periodic pressure differentials in the reservoir, further improving displacement efficiency over co-injection. These findings provide theoretical and practical guidance for designing flue gas-assisted steam flooding schemes in heavy oil reservoirs.
The significant heterogeneity of the carbonate reservoirs in the Sinian Dengying formation in the Sichuan Basin poses substantial challenges to interpretation of microresistivity scanning image logging for the fractured-vuggy reservoirs. To enhance the accuracy of imaging logging in evaluating fractured-vuggy carbonate reservoirs, a core surface electric field measurement device was customized based on AutoScan-Ⅱ core planar resistivity scanning experiments. Using this device, experiments on rock surface resistivity measurement and imaging were conducted to quantitatively analyze the imaging response characteristics of vugs and fractures. A calibration method for fracture-vug parameters based on rock surface resistivity distribution was established. The results show that the computed vug diameter and plane porosity increase linearly as the core-measured vug diameter and plane porosity increase, and the computed fracture width and the surface fracture ratio increase logarithmically as the core-measured fracture width and surface fracture ratio increase. The laboratory-based rock surface resistivity experiments effectively reduce the discrepancies between core measurements and imaging logging calculations, enabling precise calibration and quantitative evaluation of plane porosity of fractures and vugs. This study provides a methodological framework for improving the reliability and accuracy of imaging logging in evaluating fractured-vuggy reservoirs, and offers technical support for the evaluation and development of carbonate reservoirs.
The fault-controlled fractured reservoirs in the Shunbei oilfield are characterized by strong heterogeneity and complex oil-water movement patterns, making traditional homogeneous models fail to accurately characterize relative permeability. This study proposes a physical simulation method based on modular fracture networks. Regarding the characteristics of natural fractures in carbonate reservoirs, corresponding modular fracture network physical models with varying fracture complexity are designed, and the oil-water displacement experiments are conducted to obtain displacement parameters for different fracture models. On this basis, oil/water relative permeabilities are calculated, and the relative permeability charts are plotted. The obtained oil/water relative permeability curves are analyzed and validated using actual production data of wells in the fractured reservoirs to understand the variations of reservoir performance in the Shunbei oilfield.
During the development of condensate gas reservoirs, formation pressure decline leads to water invasion, which reduces gas-phase permeability in the gas-water two-phase flow system of the formation. As a result, the gas well productivity declines significantly, and in severe cases, rapid water production escalation causes water flooding, impacting the rational development and reserves estimation of the gas field. To address the early warning of water breakthrough in ultra-deep fault-controlled condensate gas reservoirs, by integrating empirical formulas, experimental simulation, and production statistics, it is determined that the produced water-gas ratio of the ultra-deep fault-controlled condensate gas wells in the Shunbei area should be less than 0.56×10?? m3/m3. Exceeding this threshold suggests a risk of premature water breakthrough. By analyzing ion contents in water samples from the condensate reservoirs in the Shunbei area, two key indicators such as Br? and I? concentrations were incorporated into the Stiff pattern diagram. A representative chart for early warning of water breakthrough in the ultra-deep fault-controlled condensate gas reservoirs in the Shunbei area was established, providing a basis for making development strategies. The field application has verified its reliability.
Fault-controlled condensate gas reservoirs in the Shunbei No.4 fault zone of Tarim Basin contain high-angle fractures, leading to the possibility of bottom water coning. The bottom water connection points and gas-water connection modes in the Shunbei No.4 fault zone were identified by combining seismic and reservoir characterization results, and the scale of the water body was evaluated using the reservoir characterization method and the material balance method. Combined with the parameters such as the energy indication curve of the gas reservoir, the water avoidance height, and the gas production rate, the water invasion risk of production wells in the Shunbei No.4 fault zone was qualitatively assessed. The on-site water control measures such as the managed liquid production for controlling water coning and the gas injection for controlling water coning have achieved satisfactory results in enhanced oil recovery.
The ultra-deep fault-controlled fractured-vuggy gas reservoirs in the Tarim Basin represent a principal option for increasing gas reserves and production. It is crucial to determine the reasonable productivity of gas wells for the efficient development of gas reservoirs. Shunbei ultra-deep fault-controlled fractured-vuggy gas reservoir is characterized by strong heterogeneity, high stress sensitivity, and varying physical properties, therefore, conventional methods for determining reasonable productivity of the reservoir need to be improved. Based on geological and production data, the reservoirs in the F1 zone of the Shunbei gas reservoir can be divided into three types: fault + cavity, fault + pore, and fault/fracture. According to the calculation by the binomial productivity equation for wells in high-pressure gas reservoirs, the fault + cavity reservoir show the highest absolute open flow potential (AOFP), followed by the fault + pore reservoir, and then the fault/fracture reservoir. The productivity test curves show 3 shapes such as linear, upward curved, and downward convex, with the reasonable choke as the largest choke within the testing range for the former two shapes, and as the choke at the inflection for the downward convex shape. The pressure drop method shows that, within the testing range, a larger reasonable choke is preferred for the fault + cavity reservoir, and a smaller reasonable choke for the fault + pore and fault/fracture reservoirs.
The ultra-deep oil and gas reservoirs in the Shunbei area have undergone multi-period hydrocarbon charging and migration, with complex oil/gas distribution patterns, making it difficult to identify reservoir fluid types. In order to accurately evaluate the fluid types in ultra-deep reservoirs in the Shunbei area, based on the data of well drilling, logging and production test, a comprehensive correction method for the key influencing factors of gaseous hydrocarbon data was established. A new method for identifying fluid types with a three-dimensional model incorporating coefficients of oil, gas and water contents was proposed. The results indicate that the comprehensive correction method based on the gray correlation algorithm for the factors affecting gaseous hydrocarbon data, such as drilling time, bit diameter, drilling fluid displacement, drilling coring, and drilling fluid density, has improved the comparability and accuracy of gaseous hydrocarbon data. Because the C1 content in typical gas layers is close to the total hydrocarbon content, and the heavy hydrocarbon content is relatively high in oil layers, while relatively low in water layers, a three-dimensional model using the coefficients of oil, gas and water contents is established to accurately determine the fluid types in ultra-deep reservoirs. The study results provide a basis for later decision-making on well drilling and oil and gas reservoir development.
