Log Response Research Articles

Research on dual lateral log simulation of shale bedding fractures under different influencing conditions

Micro scale fractures play a crucial role in facilitating the migration of oil and gas in low permeability shale reservoirs. However, the identification of such fractures is a complex task. The efficacy of the dual lateral log physical field changes as a means of identifying shale micro fractures remains uncertain. To address this issue, a three-layer shale bedding fracture model was developed using the finite element method and core and conventional logging data from eight wells, which was based on different shale reservoirs within the Yanchang Formation in the Ordos Basin. The present study examines the dual lateral log response characteristics resulting from distinct characteristics of horizontal bedding fractures, with a focus on the response mechanism. The simulation of logging response characteristics of shale and siltstone combination were utilized by core statistical data for verification purposes. The results indicate that under the lithology combination of shale and siltstone, the magnitude of the difference between the resistivity of the filled fracture and the formation resistivity, the greater the formation resistivity of the shale itself, the wider the fracture width, and the greater the difference between the apparent resistivity and the real formation resistivity. Furthermore, the suitable conditions for the detection of shale bedding fracture characteristics by dual lateral log are clarified. In the presence of effective filling, the dual lateral log has the capability to identify shale fractures at the micron scale. The findings of our study establish a theoretical framework for the identification and assessment of shale fractures, and furnish technical assistance for the optimal selection of “sweet spots” within shale reservoirs and the precise evaluation of reservoirs. This study lays a theoretical foundation for the identification and evaluation of shale fractures, and provides technical support for the optimal “sweet spot” selection of shale reservoirs and the accurate evaluation of reservoirs.

Lithofacies Characteristics and Methodology to Identify Lacustrine Carbonate Rocks via Log Data: A Case Study in the Yingxi Area, Qaidam Basin

Lacustrine carbonate reservoirs, extensively distributed in China, have extensive oil and gas exploration potential. However, such reservoirs are characterized by high content of terrigenous debris and complex lithofacies, and the resultant high difficulty in lithofacies identification severely restrains exploration expansion and efficient development, especially for the Upper Member of the Paleogene Lower Ganchaigou Formation (E32) of the Yingxi area in the Qaidam Basin, with burial depths generally greater than 4000 m. This research targets this area and develops a methodology for detailed lithofacies identification, after systematically investigating the characteristics of lithofacies and well log responses of lacustrine carbonate rocks, on the basis of a massive volume of data of cores, thin sections, and experiments of the study area. The analysis identified lithofacies in the Upper Member of the Paleogene Lower Ganchaigou Formation of the Yingxi area, namely, pack-wackestone, mudstone, laminated carbonate, muddy gypsum, and limy claystone. The analysis of well log response characteristics suggested that natural gamma ray, matrix density, and bulk density were sensitive to lithofacies. Then, for the first time, the rock fabric factor (RFF) method was proposed, and the lithofacies identification plot was based on the calculated RFF and high-definition spectroscopy log. The presented methodology was applied to 55 wells in the study area. The average accuracy of lithofacies interpretation in 14 cored wells reached 82.4%, indicating good application performance. This method improves the lithofacies identification accuracy of lacustrine carbonate rocks, which is of great significance for investigating the reservoir distribution law and guiding exploration and development.

Geological and Engineering ‘Sweet Spots’ in the Permian Lucaogou Formation, Jimusar Sag, Junggar Basin

AbstractUnconventional oil and gas resources require petrophysical logs to answer the question of how best to optimize geological and engineering ‘sweet spots’. Therefore, the establishment of a key well with comprehensive descriptions of lithology, reservoir properties, hydrocarbon‐bearing properties, electronic well log responses, source rock properties, brittleness, and in situ stress magnitude and direction is important for the effective exploration and production of unconventional hydrocarbon resources. Cores, thin sections, scanning electron microscopy (SEM) and comprehensive well log suites are used to build a key well for the Permian Lucaogou Formation, Jimusar Sag of the Junggar Basin. The results show that there are three main types of lithologies, including siltstone, mudstone and dolostone. Lithologies can be predicted using the combination of conventional well and image logs. The pore spaces consist of interparticle pores, intragranular dissolution pores and micropores. Nuclear Magnetic Resonance (NMR) T2 components longer than 1.7 ms are superposed as effective porosity. Permeability is calculated using the Coates model from NMR T2 spectra. The ratio of T2 components >7.0 ms to T2 components >0.3 ms is used to calculate oil saturation. TOC is calculated using the ΔlogR method. Brittleness index is calculated using Poisson‐Young's method, ranging from 13.42%–70.53%. In situ stress direction is determined, and in situ stress magnitudes (maximum horizontal stress SHmax, minimum horizontal stress Shmin, vertical stress Sv) are calculated using density and sonic logs. The strike‐slip stress type (SHmax > Sv > Shmin) is encountered. The key well which comprehensively includes the above seven properties is established. Geological and engineering (geomechanical) ‘sweet spots’ are then optimized from the key well by fully analyzing lithology, reservoir property, oil‐bearing potential, in situ stress magnitude and brittleness. It is hoped that the results support engineers' and geologists' decisions for the future exploitation of unconventional hydrocarbon resources.

Identification of interbedded gas hydrate and free gas using amplitude versus offset forward modelling

AbstractThe complex contacts between gas hydrate and free gas have been confirmed by gas hydrate pilot production in the Pearl River Mouth Basin, South China Sea. The laminated clay silt reservoirs have high amplitude reflections which may be filled with different saturations of gas hydrates, free gas and the coexistence between gas hydrate and free gas. To distinguish the variations of amplitude reflections caused by different reservoirs properties below the bottom simulating reflection, we combine the forward modelling, pre‐stack gathers with different incident angles and well log analysis to conduct the seismic responses. A number of geological models are established with variable saturations and different interfaces between gas hydrate and free gas. First, we analyse the seismic and well log responses at Sites W11, W01 and W17 near the production test area. Then, we perform the forward modelling to quantify the differences among seismic reflections with different saturations, thickness, incident angles and strata dips in free gas‐ or gas hydrate‐bearing geological models. We extract the seismic amplitudes along the bottom simulating reflection and other layers to compare with the amplitudes generated from forward modelling. The results indicate that the inclined intervals below the bottom simulating reflection have high amplitude, continuous reflection and polarity reversal which may be caused by thin gas reservoir and the interlayered gas hydrate and free gas with different saturations. The top interfaces of the gas hydrate‐ and free gas‐bearing layers show typical Class III amplitude versus offset and exhibit high amplitude reflections at seismic data with near, mid and far‐incident angles, which are easy to distinguish. Seismic response of far‐incident angle can be used to identify the coexistence of gas hydrate and free gas.

An intelligent identification method of interlayers in deep clastic rock – An example of Donghe Sandstone in Hade Oilfield, Tarim Basin

The identification of interlayer types is the key to improve the geological model to study the characteristics of oil and water distribution. The Donghe Sandstone in Hade Oilfield is used as the research object to calibrate the interlayer type and location by means of the outcrop, core, conventional logging curves and electrical imaging data. However, the logging response characteristics of different types of interlayers are similar, which is difficult to be accurately characterized by the conventional method. Therefore, a Random Forest (RF) intelligent method based on the Ensemble Empirical Mode Decomposition (EEMD) and Hilbert Huang Transform (HHT) is proposed to identify the type of intercalation layer. The model consists of two parts: firstly, EEMD-HHT is used to automatically identify the location of the interlayer, secondly, RF is used to classify the interlayer type. The results show that the EEMD-HHT-RF model corresponds to the results of core identification of interlayer, which can achieve rapid identification and accurate prediction in the block.

Plant functional traits and biodiversity can reveal the response of ecosystem functions to grazing

Plant functional traits can elucidate the response of plant communities and ecosystems to biotic and abiotic disturbances. However, whether livestock consume more aboveground biomass (AGB) in communities dominated by species with ‘acquisitive’ traits or in communities where biodiversity is high is not well known. Here, we measured 22 functional traits of the grazing communities and control communities in a Mongolian Plateau desert steppe. The effects of grazing on AGB, CWM traits, species diversity, and functional diversity (FD) were analysed, furthermore, we estimated the grazing impact by using the log response ratio (LRR, an increasing value shows a higher grazing impact) and investigated the correlations between the LRR, plant growth, and community-weighted mean (CWM) traits and diversity indices. We found that grazing significantly increased the CWM dry matter content and carbon-to‑nitrogen ratio and decreased the CWM height, specific leaf area (SLA), and nitrogen and phosphorus contents. The AGB decreased, while species diversity and FD increased under grazing treatments. Additionally, we found that plant traits and biodiversity could predict the response of AGB to grazing, the LRR was higher in patches dominated by species with ‘acquisitive’ foliage and in patches with higher biodiversity; in these patches, plant growth was lower. In the study area, the response of CWM traits to grazing suggests an avoidance strategy, which may be more conducive for adapting to low resource utilization environments. Also, the relationship between the CWM traits and the LRR indicated that the effect of grazing on AGB was mainly related to the selective foraging of herbivores. In addition, patches preferred by livestock may not recover quickly, leading to slow growth and thus reduced biomass under grazing treatments after prolonged grazing.

A Method for Judging the Effectiveness of Complex Tight Gas Reservoirs Based on Geophysical Logging Data and Using the L Block of the Ordos Basin as a Case Study

As an important unconventional oil and gas resource, the tight gas reservoir faces many technical challenges due to its low porosity, low permeability, and strong heterogeneity. Among them, the accurate definition of effective reservoirs and ineffective reservoirs in tight gas reservoirs directly affects the formulation and adjustment of subsequent development plans. This paper proposes a reservoir effectiveness identification method based on double factors based on conventional geophysical logging data and core experimental data. The double factors considered are based on the logging response and physical parameters of the reservoir. The identification factor F1 is obtained by using the difference in the logging response values of the natural gamma logging curve, compensated density logging curve, and acoustic time difference logging curve in different reservoirs combined with mathematical operation, and the identification factor F2 is calculated by using porosity parameters combined with Archie’s formula. The validity of the reservoir can be judged by the intersection of the above double factors. This method is applied to the Shihezi Formation in the L block, and the applicability of the double factors is compared and analyzed using the traditional method. The results show that the method has strong applicability in tight gas reservoirs and that the accuracy rate reaches 96%. Compared with the direct use of the porosity lower limit method, the accuracy of the judgment is significantly improved, and the calculation is simple, easy to implement, and unaffected by mud invasion. For study areas with different geological backgrounds, the process of this method can also be used to determine the effectiveness of the reservoir. The reservoir effectiveness identification method proposed in this paper has practical engineering significance and lays a solid foundation for subsequent fluid property identification, production calculation, and development plan formulation and adjustment.

A Multidimensional Partially Compensatory Response Time Model on Basis of the Log-Normal Distribution

In the existing multidimensional extensions of the log-normal response time (LNRT) model, the log response times are decomposed into a linear combination of several latent traits. These models are fully compensatory as low levels on traits can be counterbalanced by high levels on other traits. We propose an alternative multidimensional extension of the LNRT model by assuming that the response times can be decomposed into two response time components. Each response time component is generated by a one-dimensional LNRT model with a different latent trait. As the response time components—but not the traits—are related additively, the model is partially compensatory. In a simulation study, we investigate the recovery of the model’s parameters. We also investigate whether the fully and the partially compensatory LNRT model can be distinguished empirically. Findings suggest that parameter recovery is good and that the two models can be distinctly identified under certain conditions. The utility of the model in practice is demonstrated with an empirical application. In the empirical application, the partially compensatory model fits better than the fully compensatory model.

Fluid property identification of the Lower Cretaceous reservoirs with complex oil-water contacts in Deseo Basin, Chad

Recently, exploration breakthroughs have been made in the Lower Cretaceous sandstone reservoirs in the Doseo Basin, but the identification of reservoir fluid property is difficult due to variable reservoir lithology, complex oil-water contact within and faint responses of the oil zone, which causes the lower accuracy of reservoir fluid property identification with conventional mudlogging and wirelogging techniques. Applying the geochemical logging, fluorescent logging, mud logging and cutting logging technology, in combination with formation test data, this paper distinguishes the crude oil types, analyzes the logging response characteristics of oil zone after water washing, and establishes the interpretation charts and parameter standards for reservoir fluid properties. The crude oil can be divided into two types, namely viscous-heavy and thin-light, based on total hydrocarbon content and component concentration tested by mud logging, features of pyrolysis gas chromatogram and fluorescence spectroscopy. The general characteristics of oil layers experienced water washing include the decrease of total hydrocarbon content and component concentration from mud logging, the decrease of S1 and PS values from geochemical logging, the decrease of hydrocarbon abundance and absence of some light components in pyrolysis gas chromatogram, and the decrease of fluorescence area and intensity from fluorescence logging. According to crude oil types, the cross plots of S1 versus peak-baseline ratio, and the cross plots of rock wettability versus fluorescence area ratio are drawn and used to interpret reservoir fluid property. Meanwhile, the standards of reservoir fluid parameter are established combining with the parameters of PS and the parameters in above charts, and comprehensive multiparameter correlation in both vertical and horizontal ways is also performed to interpret reservoir fluid property. The application in the Doseo Basin achieved great success, improving interpretation ability of fluid property in the reservoir with complex oil-water contact, and also provided technical reference for the efficient exploration and development of similar reservoirs.

Novel fluid typing method of NMR dual-TW logging in mixed-wet reservoirs

In mixed wetting reservoirs, the fluids typing is difficult by using nuclear magnetic resonance (NMR) logging. The data processing and interpretation method of NMR dual-waiting time (TW) activation faces serious challenges and the previous NMR time-domain analysis (TDA) of NMR dual-TW logging for water-wet condition is not applicable. The petrophysical characteristics under mixed-wet conditions was studied and the oil-wet factor was defined, and new NMR logging response equations was investigated and the echo train difference between long and short wait times were derived. The relaxation parameters of fluids and water saturation was finally calculated by the genetic algorithm. Therefore, a new improved TDA method was proposed for mixed-wet reservoirs. To verify the method, a petrophysical model was set and some simulations proved it accurate. A case study from Chang 8, Ordos Basin, China, was studied, and the oil saturation and volume in the flushed zone were calculated. From the oil-testing results, two cross-plots for fluid typing were constructed based on the calculated oil saturation in flushed zone, T2 geomean difference of dual-TW NMR logging. The practical application shows that the novel TDA method of NMR dual-TW logging for mixed-wet reservoirs is efficient for the fluid identification.

Feature engineering process on well log data for machine learning-based SAGD performance prediction

The conventional numerical simulation requires a reliable three-dimensional reservoir model to evaluate the steam-assisted gravity drainage (SAGD) performance, but it may be time-consuming and need a significant amount of static data. This study aims to develop a machine learning (ML) model that predicts the SAGD performance based on well log data from a near single well. Although the ML model is useful in capturing underlying non-linear relationships between input features and target features, it requires a large number of training data. However, the number of data is usually small in commercial fields, limiting the availability of all log responses as input features to consider reservoir heterogeneity. In case of using small dataset, the overfitting can occur with an excessive number of model parameters. Therefore, this study introduces a feature engineering process to extract and select key features from well log data to alleviate the overfitting problem.In this study, the feature engineering process was optimized by sensitivity analysis on feature extraction and feature selection methods. For data preparation, the 63 SAGD well pairs and their matched logged wells were screened from the six commercial oil sand fields in Alberta, Canada. The SAGD process mechanism and petrophysics were considered to build data screening criteria. Each depth of the log data was categorized into pay-zone or shale barrier. For feature extraction, sampling intervals were placed on log data. This calculates the net pay thickness, averaged gamma ray, deep resistivity, and neutron porosity logs in the pay-zone. In addition, the elevation of two shale barriers and the distance between the SAGD well and logged well are extracted. Sensitivity analysis of the sampling interval length was conducted to determine the optimal conditions considering heterogeneity and feature reduction. For the feature selection, various combinations of the extracted features were used to examine their inherent meaning for predicting the SAGD performance. The multi-layer perceptron model was trained based on various selected features to predict the SAGD performance indicators of a seven-year operation. The optimal sampling interval length was determined as 10m and the combination of gamma ray, deep resistivity, shale barrier elevation, and the distance information was selected as key input features. The model showed reasonable prediction results for SAGD productivity and economic indicator with R2 of 0.67 and 0.72, respectively.

Study on pore structure characterization of strong diagenesis sandstones and the logging response characteristics in Tazhong area, Tarim Basin

The original framework of pore structure is determined by sedimentation; however, reservoirs with different rock components undergo different diagenetic processes with different intensities, so they have different pore structure characteristics. The logging response characteristics of strong diagenetic sandstone show a series of geophysical responses, such as acoustic, nuclear, and electrical, of the final pore structure style formed by diagenetic transformation after primary sedimentary structures. In low permeability reservoirs, the response characteristics are more reflected as the signal coupling of different geological factors instead of a linear correlation with porosity or permeability like in conventional reservoirs. The formation studied, the Silurian system in the Tazhong area, is mainly characterized by a large area and low abundance of lithological reservoirs with complex geological characteristics such as variable lithology, large physical property differences, and strong heterogeneity. Due to the early formation of the paleo-uplift in the Tazhong area, the Indosinian and Yanshan orogeny had negligible effects and formed a stable tectonic background. Furthermore, the evolution of pore structure is reflected in the transformation from primary pores to secondary or the remaining pores by cementation and dissolution in different diagenetic stages of different sand bodies in tidal flat faces. Therefore, the analysis and characterization of the pore structure system are particularly important. Using data based on 314 MICP samples, continuous changes of the pore structure, and the logging response in single layer and correlated layers, we conducted observations and analytics in the study. Based on the continuous MICP data, the relationship between the changes in pore structure, the geological principles, and the logging response characteristics is analysed. Our results show that the pore system heterogeneity is mainly caused by dissolution and cementation and differs in distribution. The main controlling factors of pore structure changes are transformed from sedimentation controls mainly to sedimentation–diagenesis or mainly diagenesis effects from the bottom-up case. Six types of pore structures are characterized, and we analysed the coupling effect of sedimentation and diagenesis factors on the logging response in the inconsistency features of curves. The classification of pore structure can help to analyse the law of pore structure change in sand body, and quantitatively characterize it from the perspective of control factors and logging response characteristics, which lays a foundation for the subsequent pore structure prediction.

Genetic Mechanisms and Multiparameter Logging Identification of Low-Resistivity Oil Pay: A Case Study of the Triassic Chang 6 Member, Zhidan Area, Ordos Basin, China.

Low-resistivity pay has been found throughout the world. The causes and logging responses of low-resistivity reservoirs are complex and variable. The weak variations in resistivity between the oil pay and the adjacent water pay makes it difficult to identify fluids by resistivity log analysis, which reduces the overall exploration benefit of the oil field. Therefore, it is very important to study the genesis and logging identification technology of the low-resistivity oil pay. In this paper, we first analyzed the core results such as X-ray diffraction, scanning electron microscopy, mercury intrusion, phase permeability, nuclear magnetic resonance, physical properties, electric petrophysical experiment, micro-CT, rock wettability, etc. The results show that: ① the development of low-resistivity oil pays in the studied area is mainly controlled by irreducible water saturation. The complicated pore structure, high gamma ray sandstone, and rock hydrophilicity are the factors that lead to the increase of irreducible water saturation. ② The salinity of formation water and the invasion of drilling fluid also have a certain influence on the variation of reservoir resistivity. ③ In order to magnify the difference between oil and water, sensitive parameters of logging response are extracted according to the controlling factors of low- resistivity reservoir. Then, AC-RILD, SP-PSP, GR*GR*ΔSP-RILD, and (RILM-RILD)/RILD-RILD cross-plots, some overlap method, and movable water analysis are used to identify low-resistivity oil pays synthetically. In the case study, the comprehensive application of the above identification method can effectively improve the accuracy of fluid recognition step by step. It provides reference for identifying more low-resistivity reservoirs with similar geological conditions.

Experimental measurements and response analysis of resistivity of reservoirs with complex wettability: A case study of Yan’an Formation, Ordos Basin, China

Resistivity logs are commonly used to distinguish oil and water reservoirs. However, the complex hydrocarbon accumulation pattern in the study area leads to complex wettability, which significantly affects the resistivity as well as the density and neutron logs and causes difficulties in fluid-type identification. To understand the resistivity characteristics and accurately identify the fluid types, resistivity experiments of core samples selected by the density and neutron logs are performed. The nuclear magnetic resonance (NMR) is simultaneously measured to determine the rock wettability. Instead of the conventional “aged” method for restoring the original wettability, a new set of experimental procedures is developed for obtaining resistivity and NMR [Formula: see text] spectra of samples with wettability as close as possible to that of the original reservoir. Specifically, samples with and without oil washing are measured separately, and a simple correction method for the resistivity index is developed. Moreover, the difference in the water salinity of different wells is considered. The results find that the resistivity index of samples drilled from possible oil-wet reservoirs indicated by the “abnormal” density and neutron responses varied from 2.807 to 5.388, whereas that of possible water-wet reservoirs was less than 2.0. The [Formula: see text] spectra at different states confirm the wettability of the samples. The resistivity index versus saturation ([Formula: see text]–[Formula: see text]) curves of oil-wet rocks are nearly straight lines other than the theoretical concave lines in double-logarithmic coordinates. Oil washing changes the rock wettability to varying degrees. Furthermore, the resistivity log responses of the reservoirs are accurately interpreted using the experimental data. The resistivity is simultaneously affected by the salinity, wettability, and saturation. Finally, based on the factors affecting the reservoir resistivity, fluid identification plots are established for reservoirs with different wettabilities. The agreement rates of identification using the crossplots and oil test are greater than 90%.

Emplacement dynamics of a complex thick mafic intrusion revealed by borehole image log facies analyses: Implications for fluid migration in the Parnaíba Basin petroleum system, Brazil

Sill intrusions may play a significant role in the development of petroleum systems in sedimentary basins by promoting maturation of source rocks, influencing fluid migration and acting as reservoirs, traps, and seals for hydrocarbon accumulations. Within this study, we present a novel approach to interpreting geophysical borehole data for a ca. 174 m thick sill from the Parnaíba Basin revealing new insights into both the emplacement mechanisms and impacts of the sill on hydrocarbon migration and trapping. High-resolution ultrasonic and microresistivity borehole image logs were integrated with conventional log data, petrography of eight side wall cores and total gas data recorded during drilling. The petrographic analysis revealed finer crystalline dolerite at the top and bottom layers of the sill while the upper central portion revealed coarser crystalline gabbroic facies, associated with anomalies in gamma ray, neutron porosity, sonic and geochemical log responses. From borehole image logs we interpreted key facies units including massive, fractured, cooling jointed and layered dolerite along with clear evidence for layers containing diverse inclusions interpreted as enclave structures. The integration and correlation of these data with analogue studies allowed the interpretation of gradational cooling with magmatic differentiation, partially melted host rock linked to sulphide production and organic matter maturation, mafic microgranular enclaves related to mingling processes of magma recharge, banding layers related to cumulate zones, and intense cooling fractures in the central sill body. An interval of ca. 44 m at the top of the sill with notably less jointing appears to be responsible for sealing the gas underneath, whilst the fractured central portion of the sill has enabled gas migration evidenced by increased gas signatures. In addition, this work also reveals for the first-time image log evidence for magma mingling and indications of assimilation and anatexis processes within the Parnaíba Basin. This study has important implications for improving the understanding of emplacement mechanisms of thick parallel layer intrusions and their implications for fluid flow in sedimentary basins worldwide.

Phosphorus addition increases microbial necromass by increasing N availability in China: A meta-analysis

Phosphorus (P) is an essential limiting nutrient which has a massive impact on soil organic carbon (SOC) dynamics. However, a general pattern reflecting the response of amino sugars which is an essential component of SOC to P addition in China is unclear. We conducted a meta-analysis using 24 observations in nine research publications to examine the changes in microbial necromass in response to P addition. The results indicated that P addition significantly increased total microbial (total amino sugars, TAS), fungal (glucosamine, GlcN), and bacterial (muramic acid, MurN) necromass. Effect of P addition on amino sugars depends on climate type, ecosystem type, P addition rate and P addition duration. P input can increase galactosamine (GalN), GlcN, and MurN in montane climate, whereas P addition only increased GalN and MurN in continental climates. Also, P addition significantly raised GalN and MurN in forest ecosystems, especially in plantation forests. Low P addition rates (0–50 kg P ha−1 yr−1) had positive effects on GalN and MurN. In addition, the medium P addition time (6–10 years) significantly increased GalN, GlcN, and MurN. We also found that natural log response ratio (lnRR) of soil available nitrogen (N) was positively correlated with lnRR of amino sugars suggesting that P application alleviates N limitation and reduces the uptake of N from microbial necromass leading to increased accumulation of microbial necromass. Unexpectedly, lnRR of microbial phospholipid fatty acids (PLFAs) poorly correlated with lnRR of amino sugars. This may be due to the bias caused by not having enough observations. Limited data set impeded our understanding of whether P-induced increase in amino sugars mainly attributable to increase in PLFAs and underlying mechanisms. Our meta-analysis had important implications on predicting the effect of P addition on amino sugars under different environmental conditions, providing invaluable information for soil fertility enhancement and SOC sequestration.

TOC estimation from logging data using principal component analysis

Total organic carbon (TOC) content is one of the most important parameters for characterizing the quality of source rocks and assessing the hydrocarbon-generating potential of shales. The Lucaogou Formation shale reservoirs in the Jimusaer Sag, Junggar Basin, NW China, is characterized by extremely complex lithology and a wide variety of mineral compositions with source rocks mainly consisting of carbonaceous mudstone and dolomitic mudstone. The logging responses of organic matter in the shale reservoirs is quite different from those in conventional reservoirs. Analyses show that the traditional △logR method is not suitable for evaluating the TOC content in the study area. Analysis of the sensitivity characteristics of TOC content to well logs reveals that the TOC content has good correlation with the separation degree of porosity logs. After a dimension reduction processing by the principal component analysis technology, the principal components are determined through correlation analysis of porosity logs. The results show that the TOC values obtained by the new method are in good agreement with that measured by core analysis. The average absolute error of the new method is only 0.555, much less when compared with 1.222 of using traditional △logR method. The proposed method can be used to produce more accurate TOC estimates, thus providing a reliable basis for source rock mapping.

Dose-dependent positive-to-negative shift of litter effects on seedling growth: a modelling study on 35 plant litter types

Modelling the inter-relationships between litter accumulation and plant–soil feedback is a major challenge to predict natural and agricultural ecosystem dynamics. At increasing levels of undecomposed plant litter, seedling growth tends to show a multi-faceted response trend, characterised by a peak of positive stimulation at lower dosage followed by inhibition at higher dosage. In this study, a new logistic model was developed to describe such trend and disentangle substrate-specific positive and negative effects of plant litter. The model was tested on 35 litter types applied to the common phytometer Lepidium sativum; all litter types were collected in Mediterranean shrublands of Campania region (southern Italy). Model fitting resulted to be generally higher relative to the widely used linear log response model, although in only half of the cases it also gave more parsimonious results in terms of minimising information loss. Positive and negative effects of plant litter resulted to be uncorrelated, showing that the overall trend is probably the result of the combined action of separate factors rather than the effect of a single factor behaving differently at the different doses. The results of this work provide new tools to finely tune the optimal doses in experiments on hormesis and litter phytotoxicity, through the identification of the most suited doses to centre the range of nearly linear response to litter concentration. A wide screening is also presented on the phytotoxicity profiles of a number of spontaneous plant species widely distributed in the Mediterranean area.

Reservoir classification and log prediction of gas hydrate occurrence in the Qiongdongnan Basin, South China Sea

Classifying natural gas hydrate reservoirs effectively and carrying out reservoir classification modelling is crucial, but to date, research on building artificial intelligence-assisted logging curve reservoir classification models is not abundant. As exploration and development have progressed, an increasing number of fine-grained reservoirs are being discovered, and their strong heterogeneity makes correct reservoir classification even more important. Two wells used for detecting hydrates in the Qiongdongnan (QDN) Basin are used to explore the relationship between logging response parameters and reservoir quality, as well as the method of building a logging-based reservoir classification model. Through K-means clustering and Adaboost methods, the K-means method is considered to be able to correspond to the hydrate enrichment degree, while the random forest method can establish an effective reservoir classification model (the recognition accuracy is 95%). In the different categories of reservoirs, the physical properties of the reservoirs are obviously poor, and the corresponding hydrate saturation is also low, which indicates that heterogeneity has indeed affected the enrichment of hydrates in fine-grained reservoirs. This reservoir classification research method can effectively recognize reservoirs.

Numerical Simulation of Carbon Oxygen Ratio Logging Response in Natural Gas Hydrate Reservoirs

In the process of oil and gas field development, in order to identify the gas hydrate reservoir more accurately, we try to use the carbon oxygen ratio spectrum logging technology to study the log response law of this reservoir, and compare it with the reservoir response law to better guide the oil field production. Firstly, the theoretical response law of carbon and oxygen concentration ratio of natural gas hydrate reservoir and oil layer is deduced according to the petrophysical model, and then the response law of carbon and oxygen concentration ratio of two types of reservoirs simulated by Monte Carlo numerical simulation is studied, and the similarity law and difference between the two types of reservoirs are summarized. The results show that the carbon oxygen ratio has a regular change relationship with the porosity and saturation of the reservoir. The carbon oxygen ratio can be used to preliminarily distinguish and qualitatively identify the two types of reservoirs.