Permeability Logging:A Breakthrough from 0 to1

On March 3,2024,the prototype permeability logging instrument independently developed in China successfully completed its first downhole test in Ren 91 standard well in PetroChina Huabei Oilfield.In the open hole section at a depth of 3925 metres and at a temperature of 148℃,the device collected high-quality permeability logging data.This marks a key technological breakthrough from 0 to 1 in permeability logging,and lays the foundation for the next step in developing a complete set of permeability logging equipment.

Identification of reservoir types in deep carbonates based on mixedkernel machine learning using geophysical logging data

Identification of reservoir types in deep carbonates has always been a great challenge due to complex logging responses caused by the heterogeneous scale and distribution of storage spaces.Traditional cross-plot analysis and empirical formula methods for identifying reservoir types using geophysical logging data have high uncertainty and low efficiency,which cannot accurately reflect the nonlinear relationship between reservoir types and logging data.Recently,the kernel Fisher discriminant analysis(KFD),a kernel-based machine learning technique,attracts attention in many fields because of its strong nonlinear processing ability.However,the overall performance of KFD model may be limited as a single kernel function cannot simultaneously extrapolate and interpolate well,especially for highly complex data cases.To address this issue,in this study,a mixed kernel Fisher discriminant analysis(MKFD)model was established and applied to identify reservoir types of the deep Sinian carbonates in central Sichuan Basin,China.The MKFD model was trained and tested with 453 datasets from 7 coring wells,utilizing GR,CAL,DEN,AC,CNL and RT logs as input variables.The particle swarm optimization(PSO)was adopted for hyper-parameter optimization of MKFD model.To evaluate the model performance,prediction results of MKFD were compared with those of basic-kernel based KFD,RF and SVM models.Subsequently,the built MKFD model was applied in a blind well test,and a variable importance analysis was conducted.The comparison and blind test results demonstrated that MKFD outperformed traditional KFD,RF and SVM in the identification of reservoir types,which provided higher accuracy and stronger generalization.The MKFD can therefore be a reliable method for identifying reservoir types of deep carbonates.

Facies logging identification of intermediate-basic volcanic rocks in Huoshiling Formation of Songliao Basin

Volcanic oil and gas reservoirs are generally buried deep,which leads to a high whole-well coring cost,and the degree of development and size of reservoirs are controlled by volcanic facies.Therefore,accurately identifying volcanic facies by logging curves not only provides the basis of volcanic reservoir prediction but also saves costs during exploration.The Songliao Basin is a‘fault-depression superimposed’composite basin with a typical binary filling structure.Abundant types of volcanic lithologies and facies are present in the Lishu fault depression.Volcanic activity is frequent during the sedimentary period of the Huoshiling Formation.Through systematic petrographic identification of the key exploratory well(SN165C)of the Lishu fault-depression,which is a whole-well core,it is found that the Huoshiling Formation in SN165C contains four facies and six subfacies,including the volcanic conduit facies(crypto explosive breccia subfacies),explosive facies(pyroclastic flow and thermal wave base subfacies),effusive facies(upper and lower subfacies),and volcanogenic sedimentary facies(pyroclastic sedimentary subfacies).Combining core,thin section,and logging data,the authors established identification markers and petrographic chart logging phases,and also interpreted the longitudinal variation in volcanic petro-graphic response characteristics to make the charts more applicable to this area's volcanic petrographic interpretation of the Huoshiling Formation.These charts can provide a basis for the further exploration and development of volcanic oil and gas in this area.

Application of Secondary Logging Interpretation—Taking Yan 9 Reservoir in X Area as an Example

Logging data and its interpretation results are one of the most important basic data for understanding reservoirs and oilfield development. Standardized and unified logging interpretation results play a decisive role in fine reservoir description and reservoir development. Aiming at the problem of the conflict between the development effect and the initial interpretation result of Yan 9 reservoir in Hujianshan area of Ordos Basin, by combining the current well production performance, logging, oil test, production test and other data, on the basis of making full use of core, coring, logging, thin section analysis and high pressure mercury injection data, the four characteristics of reservoir are analyzed, a more scientific and reasonable calculation model of reservoir logging parameters is established, and the reserves are recalculated after the second interpretation standard of logging is determined. The research improves the accuracy of logging interpretation and provides an effective basis for subsequent production development and potential horizons.

Development of Long-Range,Low-Powered and Smart IoT Device for Detecting Illegal Logging in Forests

Forests promote the conservation of biodiversity and also play a crucial role in safeguarding theenvironment against erosion,landslides,and climate change.However,illegal logging remains a significant threatworldwide,necessitating the development of automatic logging detection systems in forests.This paper proposesthe use of long-range,low-powered,and smart Internet of Things(IoT)nodes to enhance forest monitoringcapabilities.The research framework involves developing IoT devices for forest sound classification andtransmitting each node’s status to a gateway at the forest base station,which further sends the obtained datathrough cellular connectivity to a cloud server.The key issues addressed in this work include sensor and boardselection,Machine Learning(ML)model development for audio classification,TinyML implementation on amicrocontroller,choice of communication protocol,gateway selection,and power consumption optimization.Unlike the existing solutions,the developed node prototype uses an array of two microphone sensors forredundancy,and an ensemble network consisting of Long Short-Term Memory(LSTM)and ConvolutionalNeural Network(CNN)models for improved classification accuracy.The model outperforms LSTM and CNNmodels when used independently and also gave 88%accuracy after quantization.Notably,this solutiondemonstrates cost efficiency and high potential for scalability.

Studies on phase and group velocities from acoustic logging

It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.

Pore structure effect on reservoir electrical properties and well logging evaluation

The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.

Data mining and well logging interpretation: application to a conglomerate reservoir

Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.

Research and experimental testing of a new kind electrokinetic logging tool

We designed a new downhole electrokinetic logging tool based on numericalsimulations and petrophysical experiments. Acoustic and electric receivers cannot be arrangedat the same depth, and the proposed composite electrokinetic logging tool offers a solutionto this problem. The sound field characteristics of the detectors were tested in a water tank inthe laboratory. Then, we calculated the sound pressure of the radiated acoustic field and thetransmitting voltage response of the transmitting transducers; in addition, we analyzed thedirectivity and application of the acoustic transmitting probe based on linear phased array.The results suggest that the sound pressure generated at 1500 mm spacing reaches up to 47.2k Pa and decreases with increasing acoustic source frequency. When the excitation signalsdelay time of adjacent acoustic transmitting subarrays increases, the radiation beam of themain lobe is deflected and its energy gradually increases, which presumably enhances theacoustoelectric conversion efficiency.

A New Heat-conduction Logging Technique and its Application

The results of a heat-conduction experiment with a central point source in a sand barrel shows that the temperature of the heat source increase much faster in sand saturated with oil and air （dry sand） than in water sand. During cooling the temperature of the central heat source goes down slower in oil- or air-saturated sands than in water sands. Based on the theory of heat-conduction in porous media and the experimental results, we developed a new heat-conduction logging technique which utilizes an artificial heat source （dynamite charge or electric heater） to heat up target forma- tions in the borehole and then measure the change of temperature at a later time. Post-frac oil production is shown to be directly proportional to the size of the temperature anomaly when other reservoir parameters are fairly consistent. The method is used to evaluate potential oil production for marginal reservoirs in the FY formation in Song-Liao basin of China.

大庆油田CIFLog测井数智云平台建设应用实践

针对大庆油田生产中测井数据量大、类型多和数据来源复杂等问题,以中国石油天然气集团有限公司大型测井处理解释软件CIFLog为基础,以业务需求为主导,采用微服务架构和测井分布式云计算技术体系,研发测井大数据存储管理、中间服务层和云端测井处理解释应用等新功能,形成了大庆油田测井数智云应用平台。目前,平台已全面安装部署到大庆油田相关单位,应用效果显著。特别在大庆油田智能决策中心,平台直接用于重点水平井随钻地质导向的现场决策,大幅提升了Ⅰ类储层的钻遇率。未来平台将重点围绕新功能研发、油田数智化应用场景建设和标准化技术体系构建等开展工作,并将取得的成果及时推广复制到西南油田、塔里木油田等油气田。CIFLog云平台作为中国油气工业软件数智化建设应用的先行典范,必将发挥越来越重要的示范引领作用。

Multimineral optimization processing method based on elemental capture spectroscopy logging

Calculating the mineral composition is a critical task in log interpretation. Elementalcapture spectroscopy （ECS） log provides the weight percentages of twelve common elements,which lays the foundation for the accurate calculation of mineral compositions. Previousprocessing methods calculated the formation composition via the conversion relation betweenthe formation chemistry and minerals. Thus, their applicability is limited and the methodprecision is relatively low. In this study, we present a multimineral optimization processingmethod based on the ECS log. We derived the ECS response equations for calculating theformation composition, then, determined the logging response values for the elements ofcommon minerals using core data and theoretical calculations. Finally, a software modulewas developed. The results of the new method are consistent with core data and the meanabsolute error is less than 10%.

Processing of array sonic logging data with nulti-scale STC technique

It is desirable to develop new signal processing techniques for effectively extracting reflected waves under the strong interferences of borehole guided waves. We presented a multi-scale semblance method for the separation and velocity （slowness） analysis of the reflected waves and guided waves in borehole acoustic logging. It was specially designed for the newly developed tools with ultra-long source- receiver spacing for acoustic reflection survey. This new method was a combination of the dual tree com- plex wavelets transform （DT-CWT） and the slowness travel time coherence （STC） method. Applications to the 3D finite difference （FD） modeling simulated data and to the field array sonic waveform signals have demonstrated the ability of this method to appropriately extract the reflected waves under severe interference from the guided waves and to suppress noise in the time-frequency domain.

Fractal Correction of Well Logging Curves

It is always significant for assessing and evaluation of oil bearing layers, especially for well logging data processing and interpretation of non marine oil beds to get more accurate physical properties in thin and inter thin layers. This paper presents a definition of measures and the measure presents power law relation with the corresponded scale described by fractal theory. Thus, logging curves can be reconstructed according to this power law relation. This method uses the local structure nearby concurrent points to compensate the average effect of logging probes and measurement errors. As an example, deep and medium induced conductivity (IMPH and IDPH) curves in ODP Leg 127 Hole 797C are reconstructed or corrected. Corrected curves are with less adjacent effects through comparison of corrected curves with original one. And also, the power spectra of corrected well logging curve are abounding with more resolution components than the original one. Thus, fractal correction method makes the well logging more resoluble for thin beds.

Recognition of Milankovitch Cycles in the Natural Gamma—Ray Logging of Upper Cretaceous Terrestrial Strata in the Songliao Basin

Spectrogram analysis of seven natural gamma-ray logging of Member 1 of the Qingshankou Formation （K2qn^1） and Member 1 and 2 of the Nenjiang Formation （K2n^1-2） of Late Cretaceous age in the Songliao Basin reveals sedimentary cyclicities controlled by Milankovitch climate periodicities. The recognition of Milankovitch cycles allows estimation of an average accumulation rate of ～7.55- 8.62 cm/ka for the K2qn^1 sections, and ～6.69-10.16 cm/ka for the K2n^1-2 sections. Two marine transgression events occurred during the deposition of K2qn^1 and K2n^1-2 and their ages are at ～0.74- 1.10 Ma and ～2.38-4.84 Ma, respectively. Identification of Milankoviteh cycles from fine-grained deep lake sedimentary rocks in the Songliao Basin may provide great potential for high-resolution stratigraphic subdivisions and correlations.

Logging Geology Study of the Caverned Paleokarst Reservoir Distribution

In recent years, many carbonate rock oilfields such as Lunnan and Tahe have been found in the Tarim Basin, and the main reservoir space of the stable high yield wells in these oilfields consists mainly of the caverns formed by the paleo-karstification and the dissolution pores and fractures connected with them. Nevertheless, it is difficult to predict effectively the distribution of the cavern reservoir because of its extremely serious heterogeneity. In this paper, a case study of the Lunxi Oilfield in the north uplift of the Tarim Basin is conducted to introduce the logging geology method for predicting the distribution of the caverned paleokarst reservoir. By means of building up the logging recognition style of different caverns and differentiating and correlating the karst zones with logging curves, and through an analysis of the paleokarst topography background, the favorable karst zones and distribution areas of the high quality cavern reservoir have been located, which lays a new basis for further exploration in this area.

CCSD Well Logging Engineering Program

This paper introduces briefly the tasks and characteristics of China Continent Science Drilling (CCSD) Well Logging Engineering, the logging methods measured with CCSD, the quality control of original logging information, the logging plan of CCSD, the logging engineering management of CCSD, the logging interpretation and the results and reports made with CCSD.

Log4cxx在国产化平台的应用研究

以国产化操作系统、数据库和硬件环境为基础,通过分析和示例详细阐述了使用及扩展Log4cxx日志框架实现日志信息记录和管理的具体方法,为国产化软件的开发和维护提供了高效、可靠、易用的日志解决方案。

An impacts of logging operations on understory plants for the broadleaved／Korean pine mixed forest on Changbai Mountain, China

Natural regeneration of tree species is important to the sustainability of native forest ecosystems in the temperate zone of north- east China. This study compared the densities and heights of seedlings and the diversities of shrubs and herbs on three sites of logging op- erations: log-skidding trails (LST), logging gaps (LG) and log landing sites (LLS). Sites undisturbed by logging gaps operations were sam- pled as control. The species, counts and height of tree seedlings and the species, counts, height and percentage coverage of shrubs and herbs were recorded in the field. The highest density and greatest height of regeneration trees were observed at LG and LST. The effects of LST on the densities of broadleaved trees were greater than those of coniferous trees. The difference in seedling density between LLS and control was significant (p=0.05). There was no significant difference in average seedling height for all the tree species between the disturbed sites and control. There were more shrub and herb species at the disturbed sites than at control. The diversity of understory plants at LG was the highest among all the sites. LST and LLS were different in shrub diversity, so were LLS and control. Both LG and LLS were different from control in herb diversity. Active measures need to be taken on the operation sites to protect the coniferous trees and the diversities of under- story plants for sustaining the structure and composition of the broadleaved-Korean pine mixed forest on Changbai Mountain of China. Since different operation sites have different effects on different tree species, site-dependent actions must be taken to assure the regeneration of ecologically important tree species.

Logging Evaluation of the Ordovician Carbonate Reservoir Beds in the Lungudong Region,Tarim Basin

In recent years, great progress has been made constantly in oil and gas exploration in the Lungudong region of the Tarim Basin. However, progress has been slow in the evaluation of its main oil-producing horizons -- the Ordovician carbonate reservoir beds. Based on previous researches and on the various data such as drilling, geology and oil test, in combination with the interpretation of each single-well imaging and conventional logging data, and through analysis and comparison, the identification methods in imaging and conventional logging for four types of carbonate reservoir beds in this region are summarized in this paper. Calculation formulas for four reservoir bed parameters, i. e. shale content, porosity, permeability and oil saturation in this region are proposed; and reservoir beds in this region are divided into three levels （Ⅰ, Ⅱ and Ⅲ） by combining oil test data and logging data, The lower limits of the effective porosity of reservoir beds and the fracture porosity of effective reservoir beds are determined as 1.8% and 0.04%, respectively. The physical property parameters are calculated by conventional logging curves, and the most advantageous areas for reservoir development are predicted comprehensively. On the plane, the high-value zones of reservoir bed parameters are mainly concentrated in the N-S-trending strike-slip fault, the Sangtamu fault horst zone and near the LG38 well area; vertically, the reservoir bed parameters of the Yijianfang Formation are better than those of the Yingshan and Lianglitage formations.