Hydrocarbon Reservoirs Research Articles

Logging-data-driven lithology identification in complex reservoirs: an example from the Niuxintuo block of the Liaohe oilfield

For lithologic oil reservoirs, lithology identification plays a significant guiding role in exploration targeting, reservoir evaluation, well network adjustment and optimization, and the establishment of reservoir models. Lithology is usually predicted from well log data based on limited core observations. In recent years, machine learning algorithms have been applied to lithology identification to enhance prediction accuracy. In this paper, five algorithms, including Bayes discriminant analysis, Random Forest (RF), Support Vector Machine (SVM), Back Propagation Neural Network (BPNN), and Convolutional Neural Network (CNN) are evaluated for lithology identification using data from the Niuxintuo reservoir. This reservoir is characterized by complex structural and sedimentary features, strong heterogeneity, and intricate lithological properties, all of which present considerable challenges for well logging identification. First, we conducted a detailed observation of the core lithology. Based on the requirements for reservoir evaluation and the principles of logging identification, we reclassify the lithology of the study area into two categories: clastic rocks and dolomite. The clastic rocks are further subdivided into five rock types: fine sandstone, medium-coarse sandstone, conglomerate, mudstone, and transitional rock. The well log series were selected through sensitivity analysis. Then, Bayes discriminant analysis and four machine learning methods were trained to identify the lithology of the study area. The results indicate that except for Bayes discriminant analysis, all the constructed machine learning classifiers demonstrate high prediction accuracy, with the accuracy rate exceeding 85%. Among them, SVM classifier shows the best performance achieving a prediction accuracy as high as 93%. Additionally, the well-trained SVM model was successfully used to predict the lithology profile of blind wells. Our findings provide valuable guidance for predicting the remaining oil distribution and further exploration potential in the Niuxintuo oilfield. Furthermore, this study gains insight into the process and methodology of rapidly predicting lithology of hydrocarbon reservoirs using easily accessible well logging data.

Sediment Provenance and Facies Analysis of the Huagang Formation in the Y-Area of the Central Anticlinal Zone, Xihu Sag, East China Sea

Recent breakthrough exploration wells in the Huagang Formation in the Y-area of the central anticlinal zone of the Xihu Sag have confirmed the significant exploration potential of structure–lithology complex hydrocarbon reservoirs. However, limited understanding of the provenance system, sedimentary facies, and microfacies has hindered further progress in complex hydrocarbon exploration. Analysis of high-precision stratigraphic sequences and seismic facies data, mudstone core color, grain-size probability cumulative curves, core facies, well logging facies, lithic type, the heavy-mineral ZTR index, and conglomerate combinations in drilling sands reveals characteristics of the source sink system and provenance direction. The Huagang Formation in the Y-area represents an overall continental fluvial delta sedimentary system that evolved from a braided river delta front deposit into a meandering river channel large-scale river deposit. The results indicate that the primary provenance of the Huagang Formation in the Y-area of the Xihu Sag is the long-axis provenance of the Hupi Reef bulge in the northeast, with supplementary input from the short-axis provenance of the western reef bulge. Geochemical analysis of wells F1, F3, and G in the study area suggests that the prevailing sedimentary environment during the period under investigation was characterized by anoxic conditions in nearshore shallow waters. This confirms previous research indicating strong tectonic reversal in the northeast and a small thickness of the central sand body unrelated to the flank slope provenance system. The aforementioned findings deviate from conventional understanding and will serve as a valuable point of reference for future breakthroughs in exploration.

Dolomitization of Ordovician Kelimoli carbonates linking to shale oil formation, western Ordos Basin: new insights from magnesium and strontium isotopes

Deciphering the dolomitization process has great significance for high-quality hydrocarbon reservoir prediction in carbonate successions. The Ordovician Wulalike Formation provides shale oil in the western Ordos Basin, while lateral-contact marine dolostones of Kelimoli Formation contribute major reservoirs for extra hydrocarbons. Nonetheless, the origin and occurrence of dolostones are underexplored. Coupled with petrographic and lithologic analyses, this study attempts to investigate the dolomitizing fluid pathways and dolomitization pattern of Ordovician Kelimoli carbonates based on elemental and isotopic geochemistry. Extremely low Rb concentrations (i.e., less than 0.1) and Mn/Sr ratios (i.e., less than 2) of carbonates with micropores indicated that they are a valid proxy for geochemical signatures of coeval seawater. By contrast, dolostones developing vuggy pores showed a pronouncedly higher 87Sr/86Sr composition and Mn contents than other dolostone types, revealing that vuggy dolostones experienced meteoric water leaching and underwent geochemical alterations. Quantitative calculation of 87Sr/86Sr ratios and fluid-inclusion microthermometry revealed that the Kelimoli dolostones (i.e., dolograinstones and crystallized dolostones) were formed before meteoric water leaching influences at a deep-burial environment under seawater derivatives and sealed brine water. In evaporite–dolograinstone successions, increase in the magnesium isotopic composition (δ26Mg) with increasing burial depths indicated that the dolomitizing fluid migrated downwardly. Comprehensive isotopic evidences of 87Sr/86Sr, δ18O, and δ13C suggested that the dolomitizing fluid was a derivative of coeval seawater. In crystallized dolostone successions, upwardly heaving of δ26Mg ratios revealed that the dolomitizing fluid moved upwardly. The 87Sr/86Sr, δ18O, and δ13C and microthermometric evidence indicated that these dolostones were formed at a deep-burial, high-temperature environment and the dolomitizing fluid was derived from sealed brine water. Based on the above investigation, a comprehensive dolomitizing pattern was proposed for the studied section of Ordovician Kelimoli Formation.

Lacustrine to deltaic depositional systems: Sedimentary evolution and controlling factors of an Upper Cretaceous continental depression and implications for petroleum exploration

Lacustrine to deltaic depositional systems: Sedimentary evolution and controlling factors of an Upper Cretaceous continental depression and implications for petroleum exploration

An analytical investigation on the contributions of thermal diffusion and asphaltene to fluid distribution in hydrocarbon reservoirs

An analytical investigation on the contributions of thermal diffusion and asphaltene to fluid distribution in hydrocarbon reservoirs

Implications of solid bitumen association with low- to medium-temperature hydrothermal minerals in hydrocarbon reservoirs of Southwest China: Insights from organic petrology and sulfur isotopes

Implications of solid bitumen association with low- to medium-temperature hydrothermal minerals in hydrocarbon reservoirs of Southwest China: Insights from organic petrology and sulfur isotopes

Modeling the diffusivity of hydrogen and the associated cushion gas in depleted hydrocarbon reservoir caprocks

Modeling the diffusivity of hydrogen and the associated cushion gas in depleted hydrocarbon reservoir caprocks

Integrated geostatistical and stress-field assessment of Miocene-Pleistocene strata for offshore geologic carbon storage in the Central Gulf of Mexico

Opportunities for offshore geologic carbon dioxide (CO2) storage are promising, and assessment of subsurface stress is critical for minimizing the risk of CO2 leakage. This research aims to assess stress and temperature conditions to determine if the area has the ability for secure long-term storage. This objective was achieved by using a suite of geophysical well logs, four-arm caliper logs, geochemical data and data from the BOEM Sands Database for geomechanical stress fields assessment, borehole breakout analysis, and to build 3D simulations of reservoir pressure and fracture pressure in seven protraction areas of the Central Gulf of Mexico. Results of the geomechanical assessment demonstrate that well segments containing a high volume of breakouts will have low CO2 storage potential because pore pressure approaches the minimum horizontal stress. The reservoir temperature gradient in the continental slope reduces substantially beyond a depth of about ∼3,048 m (∼10,000 ft). The changing geothermal gradient appears to stem from a combination of cooling of shallow strata by the thermal mass of the water column above the mudline and conductive and advective heat flow associated with basal heat flow and active hydrocarbon generation and migration at depth. 3D models of stress reveal shelf sands ∼1,600 m (5,249 ft) below the seabed are in a safe CO2 storage window. Results indicate CO2 can be injected safely at a pressure below the minimum horizontal stress to minimize the risk of cross-formational flow, and the high porosity and permeability of sand units in this region can facilitate effective long-term storage of CO2 in mature hydrocarbon reservoirs and saline formations.

Sedimentology and geochemistry of Campanian–Maastrichtian sandstones of Enagi Formation, Bida Basin, Nigeria

The provenance, paleoenvironments, and mineralogical studies of the sandstones of the Enagi Formation at Gulu and Kandi in the Bida Basin were investigated for preliminary reservoir quality assessment. The average values of quartz, feldspar, and rock fragments of 76.2%, 8.7%, and 15.1% at Gulu and 59.3%, 24.6%, and 16.2% at Kandi suggest they are litharenitic and arkosic sandstones respectively. The grain size bivariate plots indicate that the Kandi and Gulu sandstones were deposited mainly within the fluvial system with low contribution from the marine and tidal environments. The moderately sorted, medium to very coarse-grained sandstone beds suggest typical braided and channel deposits while the few poorly sorted ones represent floodplain deposits. Al2O3/ TiO2, Zr/TiO2, and paleo-tectonics discriminant-function multi-dimensional diagram suggest a dominant felsic igneous origin and continental rift environment for all the samples. The sandstone beds with poorly sorted, fine-grained, immature texture and mineralogy classified as arkosic will likely have less reservoir or aquifer potential. Those beds with moderately sorted, medium to coarse-grained sub-mature texture and mineralogy classified as litharenitic represent the lithofacies with the potential to develop or maintain better porosity and permeability for a good reservoir or aquifer even at the deep subsurface. This study for the first time identified favorable geological indices for a Campanian–Maastrichtian sandstone reservoir within the Enagi Formation of the northern Bida Basin. The result of this study will further encourage exploration of the Campanian–Maastrichtian lithofacies in the West African Cretaceous rift basins for prospective underground water and hydrocarbon reservoirs.

Characteristics and distribution of tectonic fracture networks in low permeability conglomerate reservoirs

Natural fractures (particularly those reshaped by multiple tectonic stages) are of paramount importance for the development of tight conglomerate hydrocarbon reservoirs. These fractures not only enhance reservoir pore space but also serve as essential conduits for hydrocarbon migration. Focusing on the Permian Jiamuhe Formation conglomerate reservoirs in the Xiaoguai area of the Junggar Basin, this study integrates structural interpretation, core observation, and well-log evaluation to elucidate the characteristics and vertical distribution of tectonic fractures. A paleotectonic stress field numerical simulation is subsequently employed to predict their planar distribution. Results indicate that the Jiamuhe Formation primarily comprises fracture-type and fracture-porosity-type reservoirs, wherein granule and pebble conglomerates predominate. Tectonic fractures are a pivotal control on reservoir quality. They predominantly manifest as shear fractures formed under compressional stresses, with dip angles exceeding 75°, consistent with regionally extensive tectonic fractures. Such fractures are chiefly developed in fine conglomerates, gravelly sandstones, and heterogeneous sandstones adjacent to fault zones, corresponding to delta front and delta margin subfacies. Well-log interpretations suggest that fractures are more pronounced in the middle to upper sections of the Jiamuhe Formation. However, their thickness is often limited, varies considerably, and exhibits marked heterogeneity, limiting straightforward well-to-well correlations. Using the finite element numerical simulation software “2D-σ,” coupled with an elastic constitutive model and a Mohr-Coulomb failure criterion, we characterized the degree of rock failure and delineated the paleotectonic stress field and associated fracture distribution. Production data integrated with geological analyses facilitated the classification of fracture development zones into three discrete levels. Grade I fracture development zones, trending northeast–southwest (NE-SW), are predominantly subjected to northwest–southeast (NW-SE) compressive stresses and exhibit high stress values, large stress differentials, and high degrees of rock failure. A comparison of single-well production with simulation outcomes reveals that wells intersecting extensively developed fracture systems generally yield superior oil-test performances, underscoring the critical role of fractures in hydrocarbon migration and entrapment. The paleotectonic stress field numerical simulation method has thus demonstrated robust reliability for predicting tectonic fractures. Accurate identification of fracture development zones is instrumental in improving exploration success rates and optimizing hydraulic fracturing strategies during reservoir development.

Enhanced intertrace variations extraction via a self-supervised network for prestack seismic analysis

Prestack seismic analysis is crucial for characterizing subsurface geology, offering valuable insights through seismic reflections across diverse offsets or azimuths. Although existing methods have achieved notable success, they tend to primarily focus on specific intertrace differences or directly equate lateral intertrace variations with vertical waveform characteristics. This limits their potential to capture subtle nuances within geologic bodies. In this paper, we develop an innovative self-supervised neural network that enhances the extraction of comprehensive intertrace variations, enabling the more effective characterization of geologic details. Our network simulates the analytical capabilities of geologists, interpreting individual traces through their contextual relationships within the gather. We develop a unique feature mask reconstruction layer that masks the features of each trace, leveraging information from the surrounding traces for feature reconstruction. The network then reconstructs the original gather by combining these regenerated features, ensuring the completeness of the information. By focusing on feature-level analysis, the network diverges from basic data interpolation strategies, promoting a thorough extraction of intrinsic intertrace relationships. Field data experiments determine that our method surpasses conventional approaches in capturing prestack intertrace variations, facilitating more precise hydrocarbon reservoir descriptions.

Enhanced Hydrogen-Rich Syngas Production Through In-Situ Heavy Oil Gasification Process Using Nanoscale Nickel Catalyst.

With the increasing demand for clean energy, in-situ hydrogen production from hydrocarbon reservoirs has attracted increasing attention. In this work, a nanoscale nickel catalyst was prepared using the water-in-oil (w/o) microemulsion method and applied in the in-situ generation of hydrogen-rich syngas from heavy oil reservoirs. The activation energy (Ea) of the gasification reactions significantly decreased with the addition of the nickel catalyst. The catalytic effect was monitored through remarkable increases in the peak temperature values for both the low-temperature oxidation (LTO) and high-temperature oxidation (HTO) processes, and the two peaks also shifted to lower-temperature regions. Additionally, the catalyst exhibited excellent activity and selectivity during the reaction process, and therefore the highest production rate of hydrogen-rich syngas of 20.07%, combined with the peak hydrogen concentration of 5.00%, was obtained in the presence of the catalyst and water. The substantial rate of hydrogen conversion from heavy oil was calculated to be 397.87 mL/g. The preliminary results obtained in this work show that this method is a significant improvement, and the catalyst-assisted method is believed to have great potential for underground fossil fuel conversion in the future.

CigFacies: a massive-scale benchmark dataset of seismic facies and its application

Abstract. Seismic facies classification is crucial for seismic stratigraphic interpretation and hydrocarbon reservoir characterization but remains a tedious and time-consuming task that requires significant manual effort. Data-driven deep-learning approaches are highly promising for automating the seismic facies classification with high efficiency and accuracy, as they have already achieved significant success in similar image classification tasks within the field of computer vision (CV). However, unlike the CV domain, the field of seismic exploration lacks a comprehensive benchmark dataset for seismic facies, severely limiting the development, application, and evaluation of deep-learning approaches in seismic facies classification. To address this gap, we propose a comprehensive workflow to construct a massive-scale benchmark dataset of seismic facies and evaluate its effectiveness in training a deep-learning model. Specifically, we first develop a knowledge graph of seismic facies based on geological concepts and seismic reflection configurations. Guided by the graph, we then implement the three strategies of field seismic data curation, knowledge-guided synthesization, and generative adversarial network (GAN)-based generation to construct a benchmark dataset of 8000 diverse samples for five common seismic facies. Finally, we use the benchmark dataset to train a network and then apply it to two 3-D seismic data for automatic seismic facies classification. The predictions are highly consistent with expert interpretation results, demonstrating that the diversity and representativeness of our benchmark dataset are sufficient to train a network that can be generalized well in seismic facies classification across field data. We have made this dataset (https://doi.org/10.5281/zenodo.10777460, Gao et al., 2024a), the trained model, and the associated codes (https://doi.org/10.5281/zenodo.13150879, Gao et al., 2024b) publicly available for further research and validation of intelligent seismic facies classification.

Characteristics of Organic Matter Types and Organic Matter Pore Development in Marine–Continental Transitional Shale

ABSTRACTThe types of organic matter (OM) significantly impact the hydrocarbon generation potential, reservoir capacity and mechanical properties of shale. Unlike the relatively homogeneous OM in high‐maturity marine shale (predominantly solid bitumen), marine–continental transitional shale exhibits a more complex OM assemblage, comprising a mixture of marine and terrestrial kerogen (vitrinite, inertinite and liptinite) and solid bitumen. Accurate differentiation of OM types and quantification of their associated pores are critical for evaluating the reservoir properties of transitional shale formations. This study investigates the Upper Carboniferous Taiyuan Formation shale in the Ningwu Basin, a representative marine–continental transitional system. A correlative microscopy approach integrating scanning electron microscopy (SEM) and optical microscopy was employed to classify OM types, which was further augmented by image segmentation processing techniques to elucidate their pore development characteristics. It reveals disparities in pore development associated with different OM types and proposes an SEM–based identification method for distinguishing them. Results indicated that vitrinite has thick cell walls with vertical fractures, a low grayscale value and a carbon content ranging from 80% to 95%; inertinite has thinner walls with distinct protrusions, a slightly higher grayscale value than vitrinite and carbon content between 75% and 90%; liptinite often retains the morphology of residual vegetation, such as serrated cutinite, flat ring‐like sporinite and lens‐like structured alginite. Solid bitumen has the highest grayscale value and is amorphous in shape. The development of OM pores is significantly related to the OM type, with the most developed pores found in solid bitumen, which is secondary in origin. This is followed by vitrinite and inertinite, with both secondary and primary pores present. The development of pores in OM is also related to the degree of thermal evolution and the types of surrounding minerals and contact relationships. The Taiyuan Formation transitional shale in the Ningwu Basin exhibits a wide range of total organic carbon (TOC) contents, with an average of 2.14%. Its microscopic components are primarily vitrinite and inertinite (over 50%), with a low degree of thermal maturity (average 1.17%) and low content of rigid minerals (average 42.3%), resulting in poorly developed OM pores and primarily intergranular pores in the storage spaces. However, the high organic carbon content and the strong adsorption capacity of vitrinite still endow the reservoir with the ability to enrich shale gas. The transitional shale possesses unique geological features, including interspersed thin coal seams and sandstone layers. The coal generates hydrocarbons and supplies gas in conjunction with shale, whereas thin sand layers enhance the reservoir capacity of the Taiyuan Formation shale, harbouring the potential for large‐scale gas reserves. Thus, an integrated exploration and exploitation model involving coal, shale and tight sandstone is recommended to maximise the resource potential of marine–continental transitional shale.

Multi-seismic attribute analysis for reservoir facies characterisation in “Ik” field, Niger Delta, Nigeria

This study addresses the challenges of characterising hydrocarbon reservoirs in the complex depositional environment of the “Ik” field, Niger Delta Basin, Nigeria, through well log and seismic attribute analyses. Well log analysis identified three reservoirs across five wells with distinct properties. Reservoir 3 showed the most promising characteristics, including high porosity (0.22), substantial net pay thickness (73.8 m), and a favourable net pay-to-gross ratio (NpTG) (0.916), indicating excellent hydrocarbon potential. Reservoir 1 exhibited high permeability (1481.6 mD) and low shale content (0.02), despite higher water saturation (0.45), suggesting productive potential under proper management. Reservoir 2 displayed intermediate characteristics. Seismic interpretation involved synthetic seismogram generation, seismic-to-well ties, and horizon delineation corresponding to the reservoirs. Key seismic attributes, including root mean square (RMS) amplitude and sweetness, effectively delineated reservoir facies. These attributes addressed the heterogeneity of the complex geological setting in the Niger Delta by providing high-resolution lithological detail and extensive spatial coverage. High RMS amplitude and sweetness values identified interconnected sand channels and hydrocarbon-rich zones. This study demonstrates the utility of combining well log and seismic data for enhanced reservoir characterization. The findings underscore the significant hydrocarbon potential of the “Ik” field and offer valuable insights for optimizing exploration and production strategies.

Correlation between cementation exponent and pore geometry with varying pore pressure for the joint elastic-electrical modelling of porous sandstones

Summary Seismic and electrical surveys are the most employed geophysical exploration applications for understanding the subsurface earth. Differential effective medium (DEM) models are the models to interpret the seismic and electrical survey data with the greatest success. However, cementation exponent and pore aspect ratio as the indispensable geometric parameters in the electrical and elastic DEM models are independent, making the models not suitable for the joint elastic-electrical modelling, a key requirement for the joint interpretation of seismic and electrical exploration data to better understand the increasingly complex hydrocarbon reservoirs. We show how cementation exponent and pore aspect ratio are correlated in three Berea sandstone samples with changing porosity resulting from varying pore pressure. We find that cementation exponent inverted from the electrical DEM model shows a strong positive linear correlation with pore aspect ratio obtained from the elastic DEM model as an implicit function of porosity induced by increasing pore pressure. We also find that the established linear correlation can enable the DEM models to calculate one physical property (e.g., elastic or electrical) from the geometric parameter describing the other property (e.g., electrical or elastic). The results reveal how the elastic and electrical geometric parameters are linked, and provide a consistent microstructure that enables the existing elastic and electrical DEM models to be suitable for the joint elastic-electrical modelling of rocks undergoing varying pore pressure.

Investigating Pore Characteristics and Their Dependence on Shale Composition: Case Study from a Permian Basin in India.

Shale reservoirs, often acting as caprocks for conventional hydrocarbon reservoirs, exhibit moderate to high porosity and remarkably low permeability. Organic-rich shales serve as reservoirs for unconventional hydrocarbons. This study focused on evaluating the characteristics of the source rocks and the factors influencing pore parameters in organic-rich shale from a Permian Basin in India, exploring its feasibility as both a CO2 sink and a natural gas source. Experimental techniques were employed to explore the mineral and the organic matter characteristics along with attributes of the pores hosted within them. The investigated shales displayed diverse thermal maturity levels, spanning from that in oil-prone to gas-prone zones, with the total organic carbon content varying from 0.72 to 24.98 wt %, indicating substantial organic richness. Rock-Eval pyrolysis results revealed a range of thermal maturity (T max) values between 426 and 474 °C, while X-ray diffraction analysis indicated significant quantities of illite and kaolinite, along with trace amounts of pyrite in certain samples. Field-emission scanning electron microscopy imaging and its detailed interpretation provided valuable insights into the pore structure and arrangement. In our study, we found that both the clay content and the organic matter significantly contribute to gas adsorption. While clay content strongly influences mesopore attributes, the organic matter predominantly affects micropore attributes. Furthermore, a direct relationship among fractal dimension, surface area, and pore volume, indicating increased complexities with these variables. Our examination of mesopore fractal attributes revealed that smaller mesopores exhibit a more convoluted and irregular configuration in comparison to the larger ones. These findings provide significant insights into the pore morphology of the analyzed shale sample.

Performance evaluation of fracturing-huff-n-percolation-puff (FHnPP) processes in a hydrocarbon reservoir

Performance evaluation of fracturing-huff-n-percolation-puff (FHnPP) processes in a hydrocarbon reservoir

The control of effective source rocks on the distribution of hydrocarbon reservoirs in a lacustrine rift-basin: insights from a 3D basin modeling study

This study addresses the challenge of understanding hydrocarbon reservoir distribution in lacustrine rift-basins, particularly in the Fushan Depression of the South China Sea, where intricate tectonic and sedimentary dynamics complicate analysis. Effective source kitchens play a critical role in controlling hydrocarbon accumulation patterns, yet existing studies often rely on statistical methods limited by exploration biases. To overcome these shortcomings, 3D basin modeling was employed to assess the influence of effective source rocks on the distribution of hydrocarbons. The findings reveal that reservoirs in lacustrine rift-basins are closely linked to effective source rocks, exhibiting lateral migration patterns that form rings around the source kitchen, as well as vertical migration patterns concentrated above the effective source rock centers. Hydrocarbon migration is generally short-range, extending laterally up to 12 km and vertically up to 2 km. Notably, oil and gas pools are predominantly located in sedimentary facies transition zones, with key resources concentrated within a 3–6 km radius of the source rock in the lower petroleum system and at depths of 3–4 km in the upper system. This work quantitatively assesses the role of effective source rocks, offering crucial insights for future exploration in similar basins. The novelty lies in its comprehensive modeling approach, which enhances understanding of hydrocarbon distribution beyond prior statistical frameworks, providing a robust foundation for exploration and development strategies.

Time-Lapse Monitoring of Injected Fluid Migration in Hydrocarbon Reservoir using Low-Frequency Passive Seismic

Abstract Injecting fluids into wells near the reservoir is a strategy used to address tight reservoir issues. One such instance is carried out in the “TS” Oil and Gas Field. We propose low-frequency passive seismic (LFPS) measurements in continuous recording as surveillance to monitor fluid injection activities in the field and support the evaluation of connectivity between injection wells and production wells. This study utilized hydrocarbon-related spectral attributes, i.e., power spectral density – integral of Z component (PSD-IZ) and vertical-to-horizontal spectral ratio (V/H). The findings demonstrated that, consistent with anomalies, stations near the injection well had greater PSD-IZ and V/H values, especially those over the oil field. V/H max values were noticeably higher than 1, and PSD-IZ values peaked in the 2–3 Hz frequency region. Trend examination of V/H readings over three months showed injection-process-influenced fluid movement patterns. The V/H values of the stations were much higher when they were closer to the injection well and lower or even declined when they were farther away. Based on the mapping of these changes, the fluid injected from Well F is moving southward. Meanwhile, no clear indications of anomalous changes were observed for the fluid injected from Well G, likely due to differences in injection rates. This study demonstrates that the LFPS method can effectively identify the direction of injected fluid movement when the injection rate exceeds the production rate.