Log Response Research Articles

A new method of mineral inversion based on error analysis and static response equation error: A case study of a shale gas reservoir in the Wufeng-Longmaxi Formation

The accurate quantitative calculation of mineral components is very important and basic work in formation evaluation. Using well-log data to estimate mineralogy and porosity is a mainstream method with core measurements often used. However, in shale reservoirs, there are many mineral components, such as organic matter and pyrite. In addition, the pore structure is complex, and gas exists in the pores as free state, adsorbed state, and dissolved state. These factors make the logging response characteristics more complex and thus the estimation of the mineral components more difficult. To address this problem, we have adopted a mineral inversion method based on error analysis and response equation error. Based on the error analysis of the mineral inversion method, we first establish a technique to obtain interpretation parameters and the function of the response equation error combined with the core data. Then, based on the weighted total least-squares method, we construct the objective function, and we use the improved krill herd algorithm to solve the problem. Finally, we estimate the mineral component volume. The calculated results indicate that the method can accurately determine the clay, quartz + feldspar, carbonate contents, and porosity by conventional logging data. Compared to the traditional mineral inversion method, the average relative error is reduced by 11.1%. The method has high applicability to shale reservoirs and can supply the basic parameters for formation evaluation.

Rapid identification of high-quality marine shale gas reservoirs based on the oversampling method and random forest algorithm

The identification of high-quality marine shale gas reservoirs has always been a key task in the exploration and development stage. However, due to the serious nonlinear relationship between the logging curve response and high-quality reservoirs, the rapid identification of high-quality reservoirs has always been a problem of low accuracy. This study proposes a combination of the oversampling method and random forest algorithm to improve the identification accuracy of high-quality reservoirs based on logging data. The oversampling method is used to balance the number of samples of different types and the random forest algorithm is used to establish a high-precision and high-quality reservoir identification model. From the perspective of the prediction effect, the reservoir identification method that combines the oversampling method and the random forest algorithm has increased the accuracy of reservoir identification from the 44% seen in other machine learning algorithms to 78%, and the effect is significant. This research can improve the identifiability of high-quality marine shale gas reservoirs, guide the drilling of horizontal wells, and provide tangible help for the precise formulation of marine shale gas development plans.

Data-driven lithology prediction for tight sandstone reservoirs based on new ensemble learning of conventional logs: A demonstration of a Yanchang member, Ordos Basin

Lithologies are significant indicators to get deep insight of depositional and mineralogical properties of target formations, and the classic approach of achieving them is crossplot. Nonetheless, crossplot presents ineffectively when addressing classification of tight sandstone reservoirs, since most primary lithological components are characterized by similar logging responses. LightGBM (light gradient boosting machine) has been proved powerful to produce a remarkable classification, while its performance is seriously limited by the setting of hyper-parameters. LD-AFSA (linear decreasing-artificial fish swarm algorithm), an excellent solver for multi-objective optimization, then is introduced to modify the setting in a best circumstance. Besides, another integration for LightGBM is CRBM (continuous restricted Boltzmann machine), which specializes in generating less variables to speed up calculation. Consequently, a data-driven lithology predictor based on new ensemble learning is proposed, named CRBM-LD-AFSA-LightGBM. Data for validation of new predictor is cored by wells of Chang 4 + 5 member, Jiyuan Oilfield, Ordos Basin, and accordingly four experiments are designed to make a comprehensive evaluation. To highlight validating effect, SVM (support vector machine) and XGBoost (extreme gradient boosting) are adopted as competitors. Through comparison of experimental results, including prediction accuracy, F1-score, and AUC (area under curve), it is figured out that XGBoost-cored and LightGBM-cored predictors have capabilities to produce similar while more reliable results, meanwhile also exhibiting better generalization on prediction, but the computing time of latter predictor is only 1/25 shorter than that of the former. The results well demonstrate the proposed predictor plays a real high-efficient role in predicting lithologies and is deserved to receive a widespread employment in the field of logging interpretation because of its greater applicability.

Application of BP Neural Network Based on Petrophysical Big Data Mining

Based on the big data mining method of petrophysical data, this paper studies the method and application of BP neural network to establish nonlinear interpretation model in distributed cloud computing environment. The nonlinear mapping relationship between the relative objective logging response and actual formation component is established by extracting the data mining result model, which overcomes existing deficiencies of the conventional logging interpretation procedure based on the homogeneity theory, linear hypothesis and the use of statistical experience simplifying model and parameters. The results show that network prediction model has been improved and has superior reference value for solving practical problems of interpretation under complex geological conditions.

Lithology and reservoir properties of the Delaware Mountain Group of the Delaware Basin and implications for saltwater disposal and induced seismicity

ABSTRACTDeepwater siliciclastic deposits of the Delaware Mountain Group (DMG) in the Delaware Basin (DB) are the primary interval for disposal of hydraulic fracturing flowback and produced water from unconventional oil production. Understanding the storage capacity of the DMG is critical in mitigating potential risks such as induced seismicity, water encroachment on production, and drilling hazards, particularly with likely development scenarios and expected volumes of produced water. Here we present a basin-wide geologic characterization of the DMG of the Delaware Basin. The stratigraphic architecture, lithology, and fluid-flow properties including porosity, permeability, amalgamation ratios, and pore volumes, are interpreted and mapped. Lithologies are predicted using gamma-ray and resistivity log responses calibrated to basinal DMG cores and outcrop models. Sandstones exhibit the highest porosity and permeability, and sand depocenters migrate clockwise and prograde basinward throughout Guadalupian time. Permeability is highest at the top of the Cherry and Bell Canyon formations of the DMG, reaching tens to hundreds of millidarcies in porous sandstones. Porous and permeable sandstones are fully amalgamated at the bed scale, but at the channel scale, most sandstones are separated by low-permeability siltstones or carbonates where net sandstone is less than 30%. This geologic characterization can be used to assess the regional storage capacity of the DMG and as input for dynamic fluid-flow models to address pore-pressure evolution, zonal containment, and induced seismicity.

Research on Test and Logging Data Quality Classification for Gas–Water Identification

Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in the northern Ordos area. It is difficult to identify gas and water layers in the study area. In addition, in the development and production, various factors, such as the failure of the instrument, the difference in construction parameters (injected sand volume, flowback rate), poor test results, and multi-layer joint testing lead to unreliable gas test results. Then, the inaccurate logging responses will be screened by unreliable gas test results for different types of fluids. It is hard to make high-precision fluid logging identification charts or models. Therefore, this article combines gas logging, well logging, testing and other data to research the test and logging data quality classification. Firstly, we select reliable standard samples through the initial gas test results. Secondly, we analyze the four main factors which affect the inaccuracy of gas test results. Thirdly, according to these factors, the flowback rate and the sand volume are determined as the main parameters. Then, we establish a recognition chart of injected sand volume/gas–water ratio. Finally, we proposed an evaluation method for testing quality classification. It provides a test basis for the subsequent identification of gas and water through the second logging interpretation. It also provides a theoretical basis for the exploration and evaluation of tight oil and gas reservoirs.

Using the Modified Resistivity–Porosity Cross Plot Method to Identify Formation Fluid Types in Tight Sandstone with Variable Water Salinity

It is generally difficult to identify fluid types in low-porosity and low-permeability reservoirs, and the Chang 8 Member in the Ordos Basin is a typical example. In the Chang 8 Member of Yanchang Formation in the Zhenyuan area of Ordos Basin, affected by lithology and physical properties, the resistivity of the oil layer and water layer are close, which brings great difficulties to fluid type identification. In this paper, we first analyzed the geological and petrophysical characteristics of the study area, and found that high clay content is one of the reasons for the low-resistivity oil pay layer. Then, the formation water types and characteristics of formation water salinity were studied. The water type was mainly CaCl2, and formation water salinity had a great difference in the study area ranging from 7510 ppm to 72,590 ppm, which is the main cause of the low-resistivity oil pay layer. According to the reservoir fluid logging response characteristics, the water saturation boundary of the oil layer, oil–water layer and water layer were determined to be 30%, 65% and 80%, respectively. We modified the traditional resistivity–porosity cross plot method based on Archie’s equations, and established three basic plates with variable formation water salinity, respectively. The above method was used to identify the fluid types of the reservoirs, and the application results indicate that the modified method agrees well with the perforation test data, which can effectively improve the accuracy of fluid identification. The accuracy of the plate is 88.1%. The findings of this study can help for a better understanding of fluid identification and formation evaluation.

Observing Music Therapy in Dementia: Repeated Single-case Studies Assessing Well-being and Sociable Interaction

ABSTRACT Objectives This study compared behavioral expressions of momentary well-being and sociable behavior toward significant others during music therapy and regular social interaction. Methods A 10-week active music therapy intervention was provided for people living with dementia and family caregivers. A bi-phasic AB single-case design was replicated for three sessions per dyad and coded using the Observable Well-being in Living with Dementia-Scale (OWLS) and the Verbal and Nonverbal Sociable Interaction Scale-Care Receiver (VNVIS-CR). Effect sizes (Log Response Ratio) were calculated for each session and analyzed with robust cluster meta-analysis. Results Eleven dyads were included, and 32 sessions analyzed (2102 observations). Within sessions we found a 48% increase in well-being, and a 32% increase in sociable interaction during music therapy. Heterogeneity was high. Dementia severity predicted an increase in nonverbal sociable interaction (93% for moderate dementia). Depression and time did not predict any change. Conclusion The potential of music therapy to increase well-being and sociable interactions toward significant others calls for further investigation of heterogeneity and covariates. Single-case designs are demonstrated to be feasible for these investigations. Clinical implications Preference-based music therapy may alleviate some of the individual and relational consequences of living with dementia, facilitating positive emotions and connection to significant others.

Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study

Metamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metamorphic rocks interpretation using borehole geochemical data from the 4390–5089 m interval depth of the Chinese Continental Scientific Drilling Main hole. Lithological identification abilities, correlation between geochemical and geophysical logs, and build a factor model which link in situ chemical element to minerals were studied. The results show that Potassium and Thorium logs are the most discriminating logs in metamorphic rocks. Pearson correlation shows that Potassium and Thorium are the largest contributors to the gamma ray responses. Factor analysis results show a 2 factor model-where factor 1 (amphibole mineral) and factor 2 (K-feldspar mineral) described 76.261% of the variation in log responses. These statistical methods can be a very helpful tool in helping the task of geoscientists in the context of research drillings.

Visual Modeling: A Socialization-Based Intervention to Improve Nutritional Intake Among Nursing Home Residents.

Purpose Malnutrition is a widespread, dangerous, and costly condition among institutionalized older adults and can be both a contributor to and consequence of dysphagia for individuals with cognitive impairment. However, interventions to maximize intake in individuals with dementia are limited and frequently problematic, with negative implications for independence and quality of life. The goal of this study was to examine a novel, socialization-grounded intervention based on visual modeling, utilizing the theoretical underpinnings of motor resonance and mimicry. Method To examine the impact of environment on intake, data were collected from four nursing home residents (M age = 83.5 years, SD = 4.2; three women) with dementia. Weight of food and liquid intake was measured across 15 meals and three different mealtime conditions: the "baseline condition" in which the individual ate alone, the "watch condition" in which the individual ate in the company of a "mealtime buddy," and the "eat" condition in which the individual consumed a meal while the "mealtime buddy" did the same. Results Data visualization supported a weak functional relation between eating environment and amount of intake consumed across participants. Log response ratio estimates suggested a trend for increased weight of food consumed during the eat condition as compared to baseline and the eat condition as compared to the watch condition for some participants. Conclusions These results preliminarily support the benefit of a visual model for increased consumption in some individuals with dementia. The presence and magnitude of the effect across conditions varied based on individual-level factors, such as cognitive status, which has implications for implementation. Overall, this study provides initial proof of concept regarding the use of visual modeling as an intervention approach, laying the foundation for larger scale future studies.

Study on discriminant method of rock type for porous carbonate reservoirs based on Bayesian theory

Rock typing is an extremely critical step in the estimation of carbonate reservoir quality and reserves in the Middle East. In order to recognize the rock types of carbonate reservoirs in the Mishrif Formation better, classify the reservoirs accurately, and establish the permeability model in line with the study area precisely, it is necessary to study the recognition method conforming to the actual situation of the study area. The practice shows that the current recognition methods based on capillary pressure curve, flow unit and NMR logging data can effectively distinguish rock types, but a large number of accurate experimental data are required, which can only be applied in a few cored well, however, cannot be applied in the whole oil field. In this study, based on core, thin section, logging data, the sedimentary characteristics of carbonate reservoir, logging response of four rock types as well as porosity and permeability characteristics of Mishrif Formation in W are comprehensively studied. Based on Bayesian stepwise discriminant theory in multivariate statistics, the Bayesian discrimination model based on conventional logging data is established. The examining results showed that, compared with the description of logging and coring, the accuracy of Bayesian discriminant model and cross confirmation rate have achieved more than 80% for the original sample. Reliability verification showed that the matching degree of the rock type recognized in the non-cored well with the core and mud logging was as high as 90%, which matched the depositional environment of the entire region. The study results confirm the validity and generalizability of the Bayesian method to identify and predict rock types, which can be applied to the entire Middle East region to solve the problem of the lack of core data to accurately evaluate the quality of non-cored wells and accurately predict production, meeting the needs of actual reservoir evaluation and production development in the Middle East.

Determination of Horizontal In-Situ Stress Profiles and Rock Deformation Moduli in Karamay Basin Using a Multiobjective Optimization Technique

Summary We introduce a quick and cost-effective method of estimating horizontal in-situ stress profiles and rock elastic moduli vs. depth from geophysical logs taken in vertical well sections. A multiobjective optimization approach finds the optimum solution for the inversion of in-situ stresses and the rock mechanical parameters from elastic borehole deformations measured by the commonly available four-arm caliper tools. The four-arm caliper log responses also permit quality control (QC) of input and identification and classification of borehole sections that display breakouts and sloughing. The method is applied in the estimation of horizontal in-situ stress profiles and rock deformation moduli vs. depth in Karamay Basin, Northwestern China. The results have demonstrated good agreement with available field in-situ stress measurements, indicating promising broader applications of the method.

Identifying Formation Creep: Ultrasonic Bond Logging Field Examples

Summary As part of plug and abandonment (P&A) operations, several acceptance criteria need to be considered by operators to qualify barrier elements. In casing annuli, highly bonded material is occasionally found far above the theoretical top of cement. This paper aims to describe how the highly bonded material can be identified using a combination of ultrasonic logging data, validated with measurements in laboratory experiments using reference cells and how this, in combination with data from the well construction records, can contribute to lowering the costly toll of P&A operations. Ultrasonic and sonic log data were acquired in several wells to assess the bond quality behind multiple casing sizes in an abandonment campaign. Data obtained from pulse-echo and flexural sensors were interactively analyzed with a crossplotting technique to distinguish gas, liquid, barite, cement, and formation in the annular space. Within the methodology used, historical data on each well were considered as an integral part of the analysis. During the original well construction, either water-based mud (WBM) or synthetic oil-based mud (OBM) was used for drilling and cementing operations, and some formation intervals consistently showed high bonding signatures under specific conditions, giving clear evidence of formation creep. Log data from multiple wells confirm that formation behavior is influenced by the type of mud used during well construction. The log data provided information of annulus material with a detailed map of the axial and azimuthal variations of the annulus contents. In some cases, log response showed a clear indication of formation creep, evidenced by a high bond quality around the production casing where cement cannot be present. Based on observations from multiple fields in the Norwegian continental shelf, a crossplot workflow has been designed to distinguish formation from cement as the potential barrier element. NORSOK Standard D-010 (2013) has initial verification acceptance criteria both for annulus cement and creeping formation as a well barrier element, both involving bond logs; however, in the case of creeping formation, it is more stringent stating that “two independent logging measurements/tools shall be applied.” This paper aims to demonstrate how this can be done with confidence using ultrasonic and sonic log data, validated against reference barrier cells (Govil et al. 2020). Logging responses like those gathered during full-scale experiments of reference barrier cells with known defects were observed in multiple wells in the field. Understanding the phenomenon of formation creep and its associated casing bond signature could have a massive impact on P&A operations. With a successful qualification of formation as an annulus barrier, significant cost and time savings can be achieved.

Petrophysical evaluation of sandstone gas reservoir using integrated well logs and core data for the Lower Cretaceous Kharita formation, Western Desert, Egypt

This study aims to evaluate Kharita gas reservoir to enhance the production. The increase in water-cut ratio reduces the left hydrocarbons’ amount behind pipe. Accurate determination of pore throats, pores connectivity and fluid distribution are central elements in improved reservoir description. The integration of core and logging data responses is often used to draw inferences about lithology, depositional sequences, facies, and fluid content. These inferences are based on petrophysical models utilizing correlations among tools’ responses as well as rocks and fluids properties. Upper Kharita Formation produces gas and condensate from the clastic sandstone in Badr-3 field, western desert of Egypt. It consists mainly of sandstone with shale intercalations. It is subdivided into three sub-units Kharita A, Kharita B and Kharita C that are in pressure communication. Hence, a new further investigation and review for the previously calculated GIIP (gas initially in place) was initiated. The results of this study yielded that the main uncertainty in the volumetric calculations was the petrophysical evaluation; subsequently, a new unconventional petrophysical evaluation approach was performed. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. Reservoir shale cutoff of 55% by using cross-plot between shale volume and porosity (Toby Darling concept) was utilized to discriminate the reservoir from non-reservoir sections. The porosity model was used to calculate reservoir porosity, using the density log. The Archie and saturation/height function models were used to calculate the water saturation and used to calibrate the water saturation in the transition zone. The porosity–permeability (POR-PERM) transform equation was used to estimate the reservoir connectivity (absolute permeability) for the four petrophysical facies (High Quality Reservoir, Moderate Quality Reservoir, Low Quality Reservoir and Highly Shale Reservoir). Core data have shown variations in reservoir quality parameters (porosity and permeability) from one well to the other. Integration of all the reservoir pressures indicated that there are different fluid types (oil, gas and water) in the Upper Kharita Formation level. The saturation/height function model was used to calibrate the saturation in the transition zone. The integration of geological core and geophysical log data helped to conduct a comprehensive petrophysical assessment of Upper Kharita Formation for a better estimation of the reservoir and to achieve a better understanding of the water encroachment in the Upper Kharita reservoir. The big challenge is the determination of the most correct model for calculating porosity, permeability and water saturation in this reservoir of different quality sand. The new petrophysical evaluation resulted in doubling the volumes in Upper Kharita reservoir and so a perforation campaign was performed to confirm the new volumetric calculations, which showed a good match with the model results. Hence, a new well was drilled targeting the low quality sand and found them with high pressure almost near virgin pressure.

Application of continuous lithologic models in the identification of pyroclastic rocks

The lithologic profile of pyroclastic rock is based on the sedimentary environment of multiple sources, which has the characteristics of lithologic grain variation of continental clastic rock and the characteristics of rock composition from different sources. Based on the physical characteristics of the logging project, the curve value contains two aspects of rock particle size and composition information, so it is necessary to judge the transition lithology with thin thickness and complex composition according to the change relationship between upper and lower lithology. According to the variation characteristics of pyroclastic rock in the logging response of Hailaer Basin, a continuous lithologic profile variation model is established, which effectively improves the identification accuracy of transitional lithology in the lithologic profile.

Analyzing the Origin of Low Resistivity in Gas-Bearing Tight Sandstone Reservoir

Complex characteristics exist in the resistivity response of Gs reservoirs in the central inversion belt of the Xihu Sag, East China Sea Basin. Some drilling wells have confirmed the existence of abnormally low resistivity in gas reservoirs of the area; and the electrical logging response was unable to reflect fluid properties of the reservoir accurately. Therefore, it is necessary to analyze the origin of the low resistivity and determine its controlling factors. Based on experimental data of core analysis and numerical simulations of mud invasion, this study thoroughly explores the origin of low resistivity in the subject gas-bearing reservoir considering both internal and external factors. The results indicated that when there is no or a low degree of mud invasion, the fine lithology, complex pore structure, additional clay mineral conductivity, and high content of pyrite are the main internal factors driving the conditions present in the studied gas reservoir. When mud invasion occurs, the invasion of highly saline mud is the main external cause of low resistivity. The numerical simulation results indicated that a formation with good permeability and high overbalance pressure has a deep invasion depth. The resistivity around the well is obviously reduced after the invasion, and low resistivity would form easily. Combined with actual data of several wells, the main influencing factors of the reservoir’s electrical characteristics were analyzed, and the main controlling factors of low resistivity in the gas reservoirs are given. This study provides valuable support for studying the low-contrast complex reservoir conductivity mechanism. The study also offers novel ideas for accurate calculation of saturation and the meticulous evaluation of reservoir for subsequent studies.

Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs

The accurate calculation of the gas content of coalbed bed methane (CBM) reservoirs is of great significance. However, due to the weak correlation between the logging response of coalbed methane reservoirs and the gas content parameters and strong nonlinear characteristics, it is difficult for conventional gas content calculation algorithms to obtain more reliable results. This paper proposes a CBM reservoir gas content assessment method combining K-means clustering and random forest. The K-means clustering is used to divide the reservoirs and distinguish the types to establish a random forest model. Judging from the evaluation effect of the research block, the prediction accuracy of the new method is significantly higher than that of the original method, and more accurate gas content prediction values can be obtained for different types of reservoirs. Studies have shown that this method can help the gas content evaluation of CBM reservoirs, improve the accuracy of gas content evaluation, and better support the exploration and development of CBM reservoirs. The results of this study show that the random forest method based on clustering can effectively distinguish the relationship between different logging responses and gas content. On this basis, the random forest algorithm modeling can effectively characterize the complex relationship between gas content and logging curve response. In the case of poor correlation between gas content and logging curve, the gas content of the reservoir can also be accurately calculated.

Classification of Void Space Types in Fractured-Vuggy Carbonate Reservoir Using Geophysical Logging: A Case Study on the Sinian Dengying Formation of the Sichuan Basin, Southwest China

The fractured-vuggy carbonate reservoirs display strong heterogeneity and need to be classified into different types for specific characterization. In this study, a total of 134 cores from six drilled wells and six outcrops of the Deng #2 and Deng #4 members of the Dengying Formation (Sichuan Basin, Southwest China) were selected to investigate the petrographic characteristics of void spaces in the fractured-vuggy carbonate reservoirs. Four void space types (VSTs) were observed, namely the solution-filling type (SFT), cement-reducing type (CRT), solution-filling breccia type (SFBT) and solution-enlarging fractures and vugs type (SEFVT). The CRT void spaces presented the largest porosity and permeability, followed by the SEFVT, SFBT and SFT. The VSTs presented various logging responses and values, and based on these, an identification method of VSTs using Bayes discriminant analysis (BDA) was proposed. Two test wells were employed for the validation of the identification method, and the results show that there is good agreement between the identification results and core description. The vertical distribution of VSTs indicates that the SFT and SEFVT are well distributed in both the Deng #2 and Deng #4 members. The CRT is mainly found in the Deng #2 member, and the SFBT occurs in the top and middle of the Deng #4 member.

Logging identification method of depositional facies in Sinian Dengying Formation of the Sichuan Basin

The sedimentary facies/microfacies, which can be correlated with well logs, determine reservoir quality and hydrocarbon productivity in carbonate rocks. The identification and evaluation of sedimentary facies/microfacies using well logs are very important in order to effectively guide the exploration and development of oil and gas. Previous carbonate facies/microfacies identification methods based on conventional well log data often exist multiple solutions. This paper presents a new method of facies/microfacies identification based on core–conventional logs–electrical image log–geological model, and the method is applied in the fourth member of the Dengying Formation (Deng 4) in the Gaoshiti-Moxi area of the Sichuan Basin. Firstly, core data are used to calibrate different types of facies/microfacies, with the aim to systematically clarify the conventional and electrical image log responses for each type of facies/microfacies. Secondly, through the pair wise correlation analysis of conventional logs, GR, RT and CNL, are selected as sensitive curves to establish the microfacies discrimination criteria separately. Thirdly, five well logging response models and identification charts of facies/microfacies are established based on electrical image log. The sedimentary microfacies of 60 exploratory wells was analyzed individually through this method, and the microfacies maps of 4 layers of the Deng 4 Member were compiled, and the plane distribution of microfacies in the Gaoshiti-Moxi area of the Sichuan Basin was depicted. The comparative analysis of oil testing or production results of wells reveals three most favorable types of microfacies and they include algal psammitic shoal, algal agglutinate mound, and algal stromatolite mound, which provide a reliable technical support to the exploration, development and well deployment in the study area.

Genesis and petroleum geological significance of calcareous mudstone in Beier Sag

Beier sag is one of the most oil-rich sags in the south of Hailaer Basin in China. The purpose of the study is to clarify the identification characteristics and geological origin of calcareous mudstone strata in Nantun Formation of Beier sag, so as to provide new ideas for the identification and evaluation of high-quality source rocks, and to provide effective support for efficient exploration of oil and gas in the basin. The comparative analysis of logging curves and seismic reflection characteristics shows that the calcareous mudstone layer has the “three high and one low” logging response with high GR (Natural Gamma Ray), high LLD (Deep Investigate Induction Log), high AC (Acoustic) and low DEN (Rock Density), showing continuous and strong seismic reflection characteristics. Through the comparative analysis of experimental data of rock thin slice and microscopic image and organic geochemistry, the layer lithology is mainly gray-black mudstone, locally mixed with oil shale and marl, rich in calcium and algae. The layer has the high abundance of organic matter, good organic matter type ( II1-I ), high hydrocarbon-generating potential and high hydrocarbon-exhausting efficiency. It is the highest quality source rock found in Beier sag, and is the material base to form the large scale oil and gas accumulation. The formation of calcareous mudstone formed in the brackish water and wide lake basin by a wide range, represents the anoxic event early in Cretaceous period and is the significant stratigraphic correlation marker bed of the sag. In addition, this layer and the fan-delta front sand widely distributed in the lower part of Nantun Formation form the most favorable reservoir combination, which controls the plane distribution of oil and gas reservoirs. Above and below the calcareous mudstone strata, oil and gas are very rich.