Search Results (13)

Identifying inter-well connectivity is crucial for optimizing reservoir development and facilitating informed adjustments. While current engineering methods are effective, they are often prohibitively expensive due to the complex nature of reservoir conditions. In contrast, methods that utilize historical production data to identify inter-well connectivity offer faster and more cost-effective alternatives. However, when faced with incomplete dynamic data—such as long-term shut-ins and data gaps—these methods may yield substantial errors in correlation results. To address this issue, we have developed an unsupervised machine learning algorithm that integrates sparse inverse covariance estimation with affinity propagation clustering to map and analyze dynamic oil field data. This methodology enables the extraction of inter-well topological structures, facilitating the automatic clustering of producers and the quantitative identification of connectivity between injectors and producers. To mitigate errors associated with sparse production data, our approach employs sparse inverse covariance estimation for preprocessing the production performance data of the wells. This preprocessing step enhances the robustness and accuracy of subsequent clustering and connectivity analyses. The algorithm’s stability and reliability were rigorously evaluated using long-term tracer test results from a test block in an actual reservoir, covering a span of over a decade. The results of the algorithm were compared with those of the tracer test to evaluate its accuracy, precision rate, recall rate, and correlation. The clustering results indicate that wells with similar characteristics and production systems are automatically grouped into distinct clusters, reflecting the underlying geological understanding. The algorithm successfully divided the test block into four macro-regions, consistent with geological interpretations. Furthermore, the algorithm effectively identified the inter-well connectivity between injectors and producers, with connectivity magnitudes aligning closely with actual tracer test data. Overall, the algorithm achieved a precision rate of 79.17%, a recall rate of 90.48%, and an accuracy of 91.07%. This congruence validates the algorithm’s effectiveness in the quantitative analysis of inter-well connectivity and demonstrates significant potential for enhancing the accuracy and efficiency of inter-well connectivity identification. Full article

This study aimed to develop and implement a nanotechnology-based alternative to traditional tracers used in the oil and gas industry for assessing interwell connectivity. A simple and rapid hydrothermal protocol for synthesizing carbon quantum dots (CQDs) using agroindustry waste was implemented. Three commercial CQDs were employed (CQDblue, CQDgreen, and CQDred); the fourth was synthesized from orange peel (CQDop). The CQDs from waste and other commercials with spherical morphology, nanometric sizes less than 11 nm in diameter, and surface roughness less than 3.1 nm were used. These tracers demonstrated high colloidal stability with a negative zeta potential, containing carbonyl-type chemical groups and unsaturations in aromatic structures that influenced their optical behavior. All materials presented high colloidal stability with negative values of charge z potential between −17.8 and −49.1. Additionally, individual quantification of these tracers is feasible even in scenarios where multiple CQDs are present in the effluent with a maximum percentage of interference of 15.5% for CQDop in the presence of the other three nanotracers. The CQDs were injected into the field once the technology was insured under laboratory conditions. Monitoring the effluents allowed the determination of connectivity for five first-line producer wells. This study enables the application of CQDs in the industry, particularly in fields where the arrangement of injector and producer wells is intricate, requiring the use of multiple tracers for a comprehensive description of the system. Full article

The D reservoir in the Bongor Basin, southern Chad, is highly heterogeneous. In the stage of waterflood development, the injected water is seriously channeled along the dominant channel, and the water drive effect becomes worse. At the same time, due to the strong edge and bottom water, the water flooding situation is aggravated, the water cut is increased, and the development efficiency is reduced. To accurately identify the inter-well connectivity relationship, we developed a reservoir inter-well connectivity model based on the principle of inter-well connectivity and dynamic production data and reservoir geological parameters. Thus, the plane water injection split coefficient and water injection efficiency of each reservoir layer were obtained. The results are in good agreement with the calculation results of inter-well connectivity through verification with field tracer interpretation. The practical application results show that the method can increase the annual output of oil by 1.3%, which has a good oil increase effect. In this study, a model of inter-well connectivity in multi-layer sandstone reservoirs was established for the first time. The production performance of the model injection–production well was optimized in real time by a historical fitting and production optimization algorithm and then applied to real reservoirs, so that it could effectively improve the oilfield development and optimize the injection–production structure. Full article

The fracture-cavity combination structure between wells in fracture-cavity reservoirs is complex and changeable. Reliably identifying and quantitatively characterizing the fracture-cavity combination structure between wells has become an important prerequisite for flow channel adjustment in fracture-cavity reservoirs after water channeling and flooding. Aiming at the problems that it is difficult for the existing carving technology to characterize the flow characteristics of the injected fluid in the interwell fracture-cavity composite structure during the production process, and it is difficult for the existing interwell tracer proxy model to consider the specific fracture-cavity composite structure, this paper proposes a quantitative interpretation model for interwell tracers in fracture-cavity reservoirs with different architectures. Taking the Tahe fracture-cavity reservoir as the object, the matching relationship between the interwell fracture-cavity structure and the tracer curve was analyzed, and the tracer curve characteristics of five types of fracture-cavity structures were clarified. Considering the basic idea of tracing, a unified quantitative interpretation model of tracers under different fracture-cavity configurations based on branched flow channels and karst caves was deduced and established, and the input parameters required to apply the model, the parameters obtained directly by fitting, and further expandable calculated parameters were clarified. The interpretation model was used to fit, quantitatively interpret, and verify the reliability of the tracer curves of three wells in group TK411 of fracture-cavity unit S48 in the fourth area of Tahe Oilfield. The results show that the tracer curve fitting effect of each well was good, and the average relative error between the total flow rate explained by the tracer and the daily water production during the tracer monitoring period in the mine was only 3.02%, which effectively shows that the applicability and reliability of the quantitative interpretation model are established. The research results provide an effective way to apply tracer data in deep mining while improving the quantitative characterization ability of interwell tracer monitoring in fracture-cavity reservoirs. Full article

This study investigates the application of carbon quantum dots as tracers in inter-well connectivity monitoring. A new laboratory-made water-soluble carbon quantum dot fluorescent tracer (CQD-W) was studied using 3D fluorescence characterization, structural characterization, reservoir suitability evaluation, and core flow experiments. The experimental results showed that CQD-W has a size of about 2 nm, a minimum detection limit of 10⁻² mg·L⁻¹. It has good stability when the salinity is 200,000 mg·L⁻¹, the concentration of Ca²⁺ is 1000 mg·L⁻¹, the pH value is 1–9, and the temperature is 80 °C. Because CQD-W contains many functional groups, such as carboxyl and hydroxyl, it shows good water solubility and has a negative surface charge. In the process of formation flow, CQD-W has a small adsorption amount, high tracer resolution, and excellent injectivity and mobility, meaning it is less likely to cause reservoir damage. Through the study of this method, the application field of carbon quantum dots is broadened, and it is proved that the CQD-W fluorescent tracer has a high potential for application in the oil industry, laying the foundation for the popularization of this technology. Full article

The types of fractured-vuggy reservoirs are diverse, with dissolution holes and fractures of different scales as the main reservoir spaces. Clarifying the connectivity between wells is crucial for improving the recovery rate of fractured-vuggy reservoirs and avoiding problems of poor water- flooding balance and serious water channeling. A traditional dynamic connected model hardly describes the geological characteristics of multiple media, such as karst caves and fractures, which cause multiple solutions from the calculation. The static analysis is the basis for connectivity evaluation. In this study, we designed an intelligent search strategy based on an improved A* algorithm to automatically find a large-scale fractured-vuggy connected path by seismic multi-attribute analysis. The algorithm automatically evaluates the interwell-connected mode and clarifies the relationship between the static connected channel and the fractured-vuggy space configuration. Restricted by various factors, such as seismic identification accuracy, a static connectivity study can hardly determine the filling and half-filling inside the channel effectively, even if it can identify the main connectivity channels. An injection-production response analysis based on dynamic production data can more accurately reflect the reservoir’s actual connectivity and degree of filling. This paper further studies dynamic response characteristics based on multifractals combined with production data. To reduce the evaluation uncertainty, we combined the static and dynamic connected analysis results to comprehensively evaluate the main connected modes, such as large fracture connectivity, cavern connectivity, and fractured-vuggy compound connectivity. We use the Tahe oilfield as an example to carry out an automatic evaluation of the connected pattern. The comprehensive evaluation results of the new algorithm were basically consistent with the tracer test results and can better reflect the interwell space-configuration relationship. Our model has certain guiding significance for the adjustment of working measures during waterflooding in fractured-vuggy reservoirs. Full article

Insufficient understanding of the microbial communities and associated microbial processes in geological reservoirs hinders the utilization of this rich data source for improved resource management. In this study, along with four interwell tracer tests at a 1478-m deep fractured crystalline-rock aquifer, we analyzed the microbial communities in the injected and produced water by high-throughput sequencing. The microbial community similarities across boreholes during an interwell flow scenario frequently encountered in reservoir development was explored. Despite the significant tracer recoveries (~30%) in all tracer tests and the cumulatively >100,000 L of exogenous water (carrying exogenous microbes) injected into the 10-m-scale reservoir, the overall structure of produced-fluid microbiome did not increasingly resemble that of the injectate. However, producers with better connectivity with the injector (based on tracer test results) did have more amplicon sequence variants (ASVs) that overlapped with those in the injectate. We identified possible drivers behind our observations and verified the practicality of repeated microbial sampling in the context of reservoir characterization and long-term monitoring. We highlight that injector-producer microbial profiling could provide insights on the relative connectivities across different producers with a given injector, and that the associated logistical needs may be comparable or even less than that of classic tracer tests. Full article

Tracers are specific materials widely used in the modern oil and gas industry for reservoir characterization via single-well or inter-well tracer tests. We engineered new tracers and extended tracer test applications for on-site real-time well-drilling monitoring. Robust and cost-efficient fluorophores embedded into carrier matrices were developed to label drill cuttings as they were made at the drill bit face to improve drill-cutting depth correlation. These novel tracers allow for automated detection at concentrations up to the ppt level. Thus, the innovated tracers open the horizon to detect in real-time the drilling depth to enhance well placement and hydrocarbon recovery. Full article

This study reports on analyses of natural, geologic CO₂ migration paths in Farnsworth Oil Field, northern Texas, where CO₂ was injected into the Pennsylvanian Morrow B reservoir as part of enhanced oil recovery and carbon sequestration efforts. We interpret 2D and 3D seismic reflection datasets of the study site, which is located on the western flank of the Anadarko basin, and compare our seismic interpretations with results from a tracer study. Petroleum system models are developed to understand the petroleum system and petroleum- and CO₂-migration pathways. We find no evidence of seismically resolvable faults in Farnsworth Field, but interpret a karst structure, erosional structures, and incised valleys. These interpretations are compared with results of a Morrow B well-to-well tracer study that suggests that inter-well flow is up-dip or lateral. Southeastward fluid flow is inhibited by dip direction, thinning, and draping of the Morrow B reservoir over a deeper, eroded formation. Petroleum system models predict a deep basin-ward increase in temperature and maturation of the source rocks. In the northwestern Anadarko Basin, petroleum migration was generally up-dip with local exceptions; the Morrow B sandstone was likely charged by formations both below and overlying the reservoir rock. Based on this analysis, we conclude that CO₂ escape in Farnsworth Field via geologic pathways such as tectonic faults is unlikely. Abandoned or aged wellbores remain a risk for CO₂ escape from the reservoir formation and deserve further monitoring and research. Full article

In the oil and gas industry, tracers are used to estimate residual oil saturation, to indicate the location and orientation of fractures in tight reservoirs, to identify and mark the direction of fluid flow in fractured deposits, to locate faults and discontinuities, and to measure fluid movement in injection wells during drilling. The tracers should behave in a mechanically similar manner to the tested substance, e.g., formation waters, oil or gas, and, on the other hand, they should significantly differ from them in terms of chemical properties so that it is possible to identify them. One of the fluorescent tracers used in the oil and gas industry, e.g., for inter-well tests during secondary or tertiary production methods (especially during reservoir hydration), is uranine. In order to assess the effectiveness of fluid movement measurements, it is necessary to determine the uranine content in formation waters. In this study, a method was developed to determine uranine in formation water samples using high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The initial step in preparing samples for chromatographic analysis would be solid phase extraction (SPE). The method was validated and allows for the determination of uranine in formation water samples in the concentration range from 0.030 to 2.80 µg/L. The validation of the method included the analysis of factors influencing the measurement result (sources of uncertainty), determination of the linearity range of the standard curve, determination of the quantification limit of the method, and verification of the reproducibility, selectivity, stability and correctness achieved. The method developed within the study can be successfully applied in the case of the determination of uranine content in formation water samples from the oil and gas mining industry, which are often unstable and characterized by a relatively complex matrix. After validation, the method will also be applicable to the determination of uranine in matrices with a similar physicochemical composition, e.g., to assess groundwater flow in deformed carbonate aquifers or to characterize faults that act as barriers to horizontal groundwater flow. Full article

During micro-scale tracer flow in porous media, the permeability and fluid velocity significantly affect the fluid dispersion properties of the media. However, the relationships between the dispersion coefficient, permeability, and fluid velocity in core samples are still not clearly understood. Two sets of experiments were designed to study the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon in a core environment, using natural and sand-filled cores, respectively. From experimental data-fitting by a mathematical model, the relationship between the dispersion coefficient, flow velocity, and permeability was identified, allowing the analysis of the underlying mechanism behind this phenomenon. The results show that a higher volumetric flow rate and lower permeability cause a delay in the tracer breakthrough time and an increase in the dispersion coefficient. The core experimental results show that the dispersion coefficient is negatively correlated with the permeability and positively correlated with the superficial velocity. The corresponding regression equations indicate linear relations between the dispersion coefficient, core permeability, and fluid velocity, resulting from the micron scale of grain diameters in cores. The combination of high velocity and low permeability yields a large dispersion coefficient. The effects of latitudinal dispersion in porous media cannot be ignored in low-permeability cores or formations. These findings can help to improve the understanding of tracer flow in porous media, the design of injection parameters, and the interpretation of tracer concentration distribution in inter-well tracer tests. Full article

Waterflooding is less effective at expanding reservoir production due to interwell thief zones. The thief zones may form during high water cut periods in the case of interconnected injectors and producers or lead to a total loss of injector fluid. We propose to identify the thief zone by using a support vector machine method. Considering the geological factors and development factors of the formation of the thief zone, the signal-to-noise ratio and correlation analysis method were used to select the relevant evaluation indices of the thief zone. The selected evaluation indices of the thief zone were taken as the input of the support vector machine model, and the corresponding recognition results of the thief zone were taken as the output of the support vector machine model. Through the training and learning of sample sets, the response relationship between thief zone and evaluation indices was determined. This method was used to identify 82 well groups in M oilfield, and the identification results were verified by a tracer monitoring method. The total identification accuracy was 89.02%, the positive sample identification accuracy was 92%, and the negative sample identification accuracy was 84.375%. The identification method easily obtains data, is easy to operate, has high identification accuracy, and can provide certain reference value for the formulation of profile control and water shutoff schemes in high water cut periods of oil reservoirs. Full article

Many factors influence the evaluation process of thief zones. The evaluation index contains very complex information. How to quickly obtain effective information is the key to improve the evaluation quality for thief zones. Considering that the correlation and information redundancy among the evaluation indexes will seriously affect the evaluation results for the thief zone, based on the principal component analysis (PCA) method, this paper proposes a multi-layer weighted principal component analysis method (MLWPCA). Firstly, factor analysis is performed on the original data to obtain the plurality subsystems of the evaluation index. Then, a principal component is analyzed through the subsystems of the evaluation index PCA to obtain the principal component score. Finally, the subsystem is weighted by the factor score and the comprehensive thief zone score is obtained by combining the subsystem weight and the subsystem score. A case study on the Daqing oilfield shows the effectiveness of the method, verified by tracer tests when applying the MLWPCA method to evaluate the thief zone. The thief zone of the Daqing oilfield is obviously affected by effective thickness, coefficient of permeability variation and interwell connectivity. At present, there are 10 well developed thief zones and eight medium developed thief zones in Daqing oilfield. The accuracy of this method is 94.44%. Compared with PCA, this method has better pertinence in evaluating thief zones, and is more effective in determining the principle influencing factors. Full article