Predict Production Performance Research Articles

Numerical simulation on multi-stage fractured horizontal wells in shale gas reservoirs based on the finite volume method

In order to simulate the flowing of shale gas in multi-scale media, we established a mathematical model for the unsteady seepage of multi-stage fractured horizontal wells in shale gas reservoirs in consideration of the flowing characteristics of shale gas in matrix, natural fractures and large-scale artificial fractures. Grid division in the simulation region was carried out by means of nonstructural tetrahedral grid. Then, a 3D numerical model for the seepage of shale gas was established discretely using finite volume method and solved using sequence solution method. Finally, the production performance of multi-stage fractured horizontal wells in shale gas reservoirs and the reservoir pressure distribution were simulated, and the simulation results were analyzed. And the following research results were obtained. First, the gas production rates of multi-stage fractured horizontal wells calculated by this newly established numerical simulation method are basically consistent with the calculation results by the commercial numerical simulation software Eclipse, which proves that this new model is accurate and feasible. Second, the gas production rates of horizontal wells calculated by the sequential solution method are different from those calculated by the fully implicit solution method in the early production stages, but as the calculation progresses, both of them tend to be consistent, which further verifies the accuracy of this new model. Third, desorbed gas plays a supplementary role to reservoir pressure, but its function is limited, and its effect on gas production is little. As the production goes on, the percentage of desorbed gas increases gradually. Fourth, the key to the stimulation of shale-gas horizontal wells is to determine the number of fractured sections rationally and create longer artificial fractures. In conclusion, the research results are conducive to the design of stimulated reservoir volumes (SRVs) of shale gas reservoirs and the prediction of production performance of multi-stage fractured horizontal wells.

NEW DERIVED CORRELATIONS FOR LIBYAN CRUDE OIL TO ESTIMATE BUBBLE-POINT PRESSURE

The key factor of all petroleum engineering calculation is the knowledge of the PVT (Pressure, Volume, Temperature) parameters, such as determination of oil and gas flowing properties, predicting production performance in the future, production facilities designing and enhanced oil recovery planning methods. Those PVT properties are ideally determined experimentally in the laboratory. However, some of these experimental data is not always available; consequently, empirical correlations are used to estimate them. Many researchers have been focusing on models for predicting reservoir fluid properties from the available experimental PVT data, such as reservoir pressure, temperature, crude oil API gravity, gas oil ratio, formation volume factor, and gas gravity. The present study compares between some of the available empirical PVT correlations for estimating the bubble point pressure of some Libyan crude oils based on 35 data point samples from different Libyan oil fields. In the second part of this study, a new correlation has been derived to predict the bubble point pressure using Eviews software and compares the output results of this new correlation with some derived correlations found in the literature using statistical analysis such as the Average Absolute Error (AARE). The results showed an AARE as low as 8.7%, for bubble point pressure estimated by this new derived correlation. These results are valid to compare to other driven empirical correlations that have been evaluated.

EVALUASI RESERVOIR BATURAJA PADA LAPANGAN FALCON DENGAN MENGGUNAKAN SIMULASI RESERVOIR UNTUK MEMAKSIMALKAN PRODUKSI

Falcon Field begins with the discovery of the GG-1 wells are explored in August 1974. The program DST performed on one zone at Falcon Field in the Baturaja Formation producing 429 BOPD and 0.14 MMCFD. Then in 1978, Falcon Field was developed by constructing three wells on the platform GGA and in 1988 made eight more wells on the platform GGB. Falcon Field is thepeak production in 1978 amounted to 5670 BOPD. Currently Falcon Field still in production of 1000 BOPD and 451 MCFPD of four wells. Cumulative production in January 2014 at 10.57 and 9.08 MMCF MMBO, and Recovery Factor is currently at 19.2%. Based on the structure map and well log correlation, Baturaja in Falcon Fields has anticline structure with orientation North-South fault. The thickness of zone has 1000 ft (~300 m) with oil column around 100 ft.To conduct field production performance predictions in the future, needs to be done the reservoir simulation modeling where the results are expected to represent the true reservoir model. Grid made in this model has a cell size of 50 mx 50 m with a thickness of 3 ft, 53 layers, and a total of about 650000 cell active cell. In the early, the validation of model is carried out for the initialization by using the Black Oil Simulator model. Initialization is intended to build initial equilibrium of the total hydrocarbon reservoir with the volume control of hydrocarbon static model calculations.The alignment stages of model or History Matching is done to see if the reservoir model that has been created to represent the actual condition of the reservoir. From the simulation reservoir the number of OOIP is 55.07 MMSTB, while OOIP with the static model is 55.2 MMSTB with a difference of 0.2 %.For the development of the Falcon Fields in the Reservoir Baturaja, the study was performed under planned five scenarios, namely the first scenario (base case), the second scenario (base case with the addition of rework moving field), the third scenario (Base case with wellwork and infill), the fourth scenario (Modeling Drawdown), and the fifth scenario (Modeling Downhole Water Sink). Scenario production started in January 2014 until January 2037 for 23 years with the aim to provide maximum drainage. Falcon Field production forecasting results for the first scenario, the second scenario, the third scenario, the fourth scenario, and scenarios fifth consecutive MMSTB of 12.87, 14.66 MMSTB, 15.3 MMSTB, MMSTB 14.01, 14.17 MMSTB with consecutive RF 23:37%, 26.62% , 27.78%, 25.44%, and 25.73%.

Prediction of production performance by comprehensive methodology for hydraulically fractured well in coalbed methane reservoirs

Production data from hydraulically fractured well in coalbed methane (CBM) reservoirs was analysed using decline curve analysis (DCA), flow regime analysis, and flowing material balance to forecast the production performance and to determine estimated ultimate recovery (EUR) and timing for applying the DCA. To generate synthetic production data, reservoir models were built based on the CBM properties of the San Juan Basin and Appalachian Basin. Production data analysis shows that the transient flow (TF) occurs for 1~3 years in the vertical well and 6~16 years in the horizontal well and then the boundary dominated flow (BDF) was reached. In the TF period, it is impossible to forecast the production performance. In case of vertical well, if the production data are available for more than three years after the BDF has been reached, the production rate and EUR can be predicted with EUR error of approximately 5%. In the case of a horizontal well, the prediction can be conducted using the production data of more than a year after reached BDF with EUR error of approximately 5%. [Received: January 30, 2016; Accepted: February 3, 2017]

Prediction of production performance by comprehensive methodology for hydraulically fractured well in coalbed methane reservoirs

Production data from hydraulically fractured well in coalbed methane (CBM) reservoirs was analysed using decline curve analysis (DCA), flow regime analysis, and flowing material balance to forecast the production performance and to determine estimated ultimate recovery (EUR) and timing for applying the DCA. To generate synthetic production data, reservoir models were built based on the CBM properties of the San Juan Basin and Appalachian Basin. Production data analysis shows that the transient flow (TF) occurs for 1~3 years in the vertical well and 6~16 years in the horizontal well and then the boundary dominated flow (BDF) was reached. In the TF period, it is impossible to forecast the production performance. In case of vertical well, if the production data are available for more than three years after the BDF has been reached, the production rate and EUR can be predicted with EUR error of approximately 5%. In the case of a horizontal well, the prediction can be conducted using the production data of more than a year after reached BDF with EUR error of approximately 5%. [Received: January 30, 2016; Accepted: February 3, 2017]

Neuro-Adaptive Learning Approach for Predicting Production Performance and Pressure Dynamics of Gas Condensation Reservoir

In Reservoir Engineering, state-of-the-art data analysis enables engineers to characterize reservoirs and plan for developing fields. This allows production companies to save huge amounts that would otherwise be allocated to reservoir modelling and simulation and well testing. Numerical reservoir modelling and simulation is the standard use in industries today for comprehensive study of fields. However, the inflexible behaviour, development time and cost of numerical simulators are major challenges to production engineers, managers as well as modellers. On the other hand, Artificial Intelligence (AI) based reservoir models are characterised with low cost of development, short development time and fast tract analysis and flexibility to estimate the uncertainties normally found in numerical simulators. In this study, a strategy for controlling gas production and pressure drop in gas condensate reservoir is described. Numerical simulations of production rate and pressure drop were carried out first and their results were saved. An Adaptive Neuro-Fuzzy system was then developed and trained with some parts of the numerical simulation results. This AI-based system is checked and tested with part of the numerical simulation results that had not been used during the training. The developed system regenerates the numerical simulation results for both production rates and pressure drop at different Bottom Hole Pressures (BHPs) with very high accuracy (>98%). Results of this study showed that AI-based reservoir simulation can be considered a vital tool of help to production engineers, managers and modellers for a quick and more informed decision as regards field development plans that can meet operational targets.

Guest Editorial: Growth in Unconventional Resources Adds to Technical Literature

Guest editorial Unconventional resources require technologies typically not used to produce conventional oil and gas reservoirs. In particular, starting in the late 1990s, the combination of horizontal wells and multistage hydraulic fracturing has been key to rapidly increasing success in exploiting unconventional resources. While the well completions in unconventional resources may be more expensive than those typically applied in conventional reservoirs, the advantage is access to the very large volumes of these resources, which include tight (low-permeability) gas in sandstone or carbonate rock, coalbed methane, and organic-rich source rocks classed as shale gas and tight oil. The exploitation of shale gas, along with tight gas and coalbed methane, enabled a stunning increase in US natural gas production of approximately 4 Tcf/D from 2005 to 2010. A similar story followed a few years later for US crude oil production. Tight oil production ramped up nearly 5 million B/D over approximately 5 years, starting in 2008, and continues to rise. And it is not just the US that is benefiting—unconventional resource development is now beginning to spread to other countries around the world. The technologies that accomplished these near miracles were developed, implemented, and continue to be improved largely by SPE members, and this has been reflected in an upsurge in conference presentations and journal publications related to unconventional resources over the past decade. This is illustrated by the chart (Fig. 1), which shows a dramatic increase in the percentage of peer-reviewed papers related to unconventional resources published in SPE Reservoir Evaluation & Engineering (SPEREE) beginning in 2011. Before 2011, there were only a handful of publications related to unconventional resources each year, primarily dealing with coal-bed methane and fundamentals of fluid flow in tight pore systems. Beginning in 2011, publications related to the analysis and prediction of shale gas reservoir production performance showed a sharp increase, followed a few years later by publications related to tight oil reservoir performance analysis and prediction. In addition, enhanced oil recovery from tight oil reservoirs has become an increasing area of focus. This year, over half of the publications in SPEREE will be related to unconventional resources. As further indication of the increasing importance of unconventional resources, in July SPE released Unconventional Gas and Tight Oil Exploitation, the first SPE monograph devoted exclusively to the topic.

EVALUASI RESERVOIR BATURAJA PADA LAPANGAN FALCON DENGAN MENGGUNAKAN SIMULASI RESERVOIR UNTUK MEMAKSIMALKAN PRODUKSI

Falcon Field begins with the discovery of the GG-1 wells are explored in August 1974. The program DST performed on one zone at Falcon Field in the Baturaja Formation producing 429 BOPD and 0.14 MMCFD. Then in 1978, Falcon Field was developed by constructing three wells on the platform GGA and in 1988 made eight more wells on the platform GGB. Falcon Field is the peak production in 1978 amounted to 5670 BOPD. Currently Falcon Field still in production of 1000 BOPD and 451 MCFPD of four wells. Cumulative production in January 2014 at 10.57 and 9.08 MMCF MMBO, and Recovery Factor is currently at 19.2%. Based on the structure map and well log correlation, Baturaja in Falcon Fields has anticline structure with orientation North-South fault. The thickness of zone has 1000 ft (~300 m) with oil column around 100 ft. To conduct field production performance predictions in the future, needs to be done the reservoir simulation modeling where the results are expected to represent the true reservoir model. Grid made in this model has a cell size of 50 mx 50 m with a thickness of 3 ft, 53 layers, and a total of about 650000 cell active cell. In the early, the validation of model is carried out for the initialization by using the Black Oil Simulator model. Initialization is intended to build initial equilibrium of the total hydrocarbon reservoir with the volume control of hydrocarbon static model calculations. The alignment stages of model or History Matching is done to see if the reservoir model that has been created to represent the actual condition of the reservoir. From the simulation reservoir the number of OOIP is 55.07 MMSTB, while OOIP with the static model is 55.2 MMSTB with a difference of 0.2 %. For the development of the Falcon Fields in the Reservoir Baturaja, the study wasperformed under planned five scenarios, namely the first scenario (base case), the second scenario (base case with the addition of rework moving field), the third scenario (Base case with wellwork and infill), the fourth scenario (Modeling Drawdown), and the fifth scenario (Modeling Downhole Water Sink). Scenario production started in January 2014 until January 2037 for 23 years with the aim to provide maximum drainage. Falcon Field production forecasting results for the first scenario, the second scenario, the third scenario, the fourth scenario, and scenarios fifth consecutive MMSTB of 12.87, 14.66 MMSTB, 15.3 MMSTB, MMSTB 14.01, 14.17 MMSTB with consecutive RF 23:37%, 26.62% , 27.78%, 25.44%, and 25.73%.

Pressure transient analysis for asymmetrically fractured wells in dual-permeability organic compound reservoir of hydrogen and carbon

In this paper, a comprehensive semi-analytical model was presented to investigate pressure transient behavior for asymmetrically fractured wells in organic compound reservoir of hydrogen and carbon with dual-permeability behavior. Stehfest inversion algorithm can be used to transform it back into time domain to obtain pressure solution. The presented solution was validated well with numerical solutions. Flow characteristics for asymmetrically fractured wells in dual-permeability organic compound reservoir of hydrogen and carbon were divided into five regime. The effects of some important parameters on dimensionless pressure and its derivative curves were analyzed in details, including inter-porosity flow coefficient from matrix to natural fractures λ, storage coefficient ω, fracture asymmetry factor θ and permeability ratio κ. The presented model can be used to predict production performance and do well test analysis in the development of dual-permeability organic compound reservoir of hydrogen and carbon.

Framework for Operational Performance Measurements in Small and Medium Scale Industries Using Discrete Event Simulation Approach

Globally, production systems must cope with limitations arising from variabilities and complexities due to globalization and technological advancements. To survive in spite of these challenges, critical process measures need to be closely monitored to ensure improved system performance. For production managers, the availability of accurate measurements which depict the status of production activities in real time is desired. This study is designed to develop an operational data decision support tool (ODATA-DST) using discrete event simulation approach. The work-in-process and processing time of each workstation/buffer station in a bottled water production system were investigated. The status of each job as they move through the system was used to simulate a routing matrix. The production output data for 50cl and 75cl product from 2014-2016 were collected. A mathematical model for routing jobs from the point of arrival to the point of departure was developed using discrete event simulation. A graphical user interface (GUI) was designed based on the factory’s performance measurement algorithm. Simulating the factory’s work-in-process with respect to internal benchmarks yielded a cycle time of 4.4, 6.23, 5.04 and throughput of 0.645, 0.455, 0.637 for best case scenario, worst case scenario and practical worst case scenario respectively. The factory performed below the simulated benchmark at 26%, 28%, 28% for the 50cl and at 51%, 54%, 59% for 75cl regarding the year 2014, 2015 and 2017 respectively. Performance measurement decision support tool has been developed to enhance the production manager’s decision making capability. The tool can improve production data analysis and performance predictions.

A three-dimensional approach to model steam chamber expansion and production performance of SAGD process

SAGD is an effective technology that was devised for the development of oil sand. However, nowadays, most research is focused on the two-dimensional (2D) vertical profile, which ignores the non-uniformity of steam along the horizontal well occurring in an oilfield. In this paper, based on the properties in MacKay River oil sands, an experimental device for SAGD is well-designed to investigate steam-chamber expansion along the horizontal well. Then, based on experimental results, a new 3D mathematical model considering steam non-uniformity was established to predict production performance and steam-chamber expansion. Next, the calculated production performance and steam-chamber evolution were compared with numerical data to verify the accuracy of the model. Finally, the model was compared with previous models to assess its quality. Results show the following. (a) The steam distribution along the horizontal direction is non-uniform; even the preheating of SAGD is uniform using the modified pre-heating method, which, when switched to formal SAGD production, also presents the same non-uniform steam distribution. (b) The comparisons reveal that the proposed 3D model is reasonably more accurate than previous models in predicting cumulative oil prediction and steam-chamber expansion. (c) Factors influencing steam distribution along the horizontal well are also discussed, and it is believed that steam quality is the deciding factor that determines the degree of steam non-uniformity.

Predicting production performance of Coalbed Methane reservoirs with Long Short-Term Memory Networks

Coalbed Methane (CBM) is a clean and highly efficient energy source. The prediction of its production performance is difficult because of the complex geological conditions and exploitation processes. The CBM well deliquification always has a long duration. Therefore, long-term prediction is more instructive than short-term prediction for fracturing treatment parameters. But there is a long-term dependence problem in the time series prediction. Therefore, in this paper long short-term memory networks (LSTM) are proposed to overcome the problem. The experimental results show that in the case of similar accuracy, the LSTM predict longer than artificial neural networks. And the LSTM are more accurate than the artificial neural networks in the same output time period.

Scheme configuration design for micro-assembly system based on product family and performance

ABSTRACTIn order to respond quickly to customer demand in micro-assembly system design, a configuration design method is proposed based on product family and performance simulation. In presented method, product scheme is generated rapidly by configuration reasoning based on product family model, which integrated with multi-domain knowledge. The product performance prediction is achieved based on simulation model that is established automatically with Modelica language. The multi-domain knowledge, which is expressed by feature parameters and constraints, is fused into the product family model, and the process of configuration reasoning and performance simulation are presented. The realization of configuration design guarantees flexibility of structure design and production of micro-assembly system. Finally, the feasibility of the method is verified on a developed mechanical arm of micro-assembly system.

Technology Evolution Prediction Using Lotka–Volterra Equations

During the development planning of a new product, designers and entrepreneurs rely on the prediction of product performance to make business investment and design strategy decisions. Moore's law and the logistic S-curve model help make such predictions but suffer several drawbacks. In this paper, Lotka–Volterra equations are used to describe the interaction between a product (system technology) and the components and elements (component technologies) that are combined to form the product. The equations are simplified by a relationship table and maturation evaluation in a two-step process. The performance data of the system and its components over time are modeled by simplified Lotka–Volterra equations. The methods developed here allow designers, entrepreneurs, and policy makers to predict the performances of a product and its components quantitatively using the simplified Lotka–Volterra equations. The methods also shed light on the extent of performance impact from a specific module (component technology) on a product (system technology), which is valuable for identifying the key features of a product and for making outsourcing decisions. Smartphones are used as an example to demonstrate the two-step simplification process. The Lotka–Volterra model of technology evolution is validated by a case study of passenger airplanes and turbofan aero-engines. The case study shows that the data fitting and predictive performances of Lotka–Volterra equations exceed those of extant models.

Hydromechanics Model of Natural Gas Transport in Stress-sensitive Dual-porosity Medium

The assumption of constant permeability is not strictly applicable to porous media where rock properties undergo changes, such as stress-sensitive gas reservoirs. This study developed a hydromechanics model of a horizontal well in dual-porosity media considering the stress-sensitivity effect. The solution methods include variable substitution, perturbation technique, Laplace transformation, Sturm-Liouville eigenvalue theory, orthogonal transformation and numerical inversion. The results showed that the production rate decreases with the increasing of permeability modulus and the derivative curve will be warped up during the whole system late radial flow stage. The research has both theoretical and practical significance in predicting production performance and evaluating underground fluid transport in such formations.

Study on the relations between controlling mechanisms and dissociation front of gas hydrate reservoirs

It is significant to understand the dissociation front of gas hydrate reservoirs not only for the prediction of production performance but also for the control of geological hazards. However, great differences can be found among dissociation modes and features of dissociation front advance reported in the literature. In this study, controlling mechanisms, i.e., fluid flow, heat transfer, and hydrate dissociation, are introduced to analyze the dissociation front of a one-dimensional (1D) hydrate reservoir conditioned to depressurization. The relations between the controlling mechanisms and hydrate dissociation modes as well as the features of dissociation front advance have been identified by use of 12 well-designed scenarios considering different thermal boundary conditions, intrinsic permeability, and hydrate dissociation models. Note that the exponential function has been used to quantify the features of dissociation front advance curves that are in a convex shape. It has been revealed that a piston-like dissociation mode is formed while the dissociation of hydrate reservoirs is controlled by either the fluid flow mechanism or the heat transfer mechanism. Regarding the fitting exponent of dissociation front advance curve, it ranges from 0.5 to 1.0 for the fluid flow controlling mechanism and floats around 0.5 for the heat transfer controlling mechanism. Given that hydrate dissociation is the controlling mechanism, an extending non-piston-like dissociation mode emerges and the advance of dissociation front accelerates at the late stage. Furthermore, the dynamic variations of dissociation modes and features of dissociation front advance curves have been investigated when the controlling mechanism is changed. The dissociation mode tends to transfer from a piston-like one to a non-piston-like one and the convex shape of dissociation front advance curve is inclined to change to a concave one when the dominance of fluid flow mechanism is alleviated. Consequently, a pragmatic criterion has been developed to estimate the controlling mechanisms based on dissociation modes and advance features of dissociation front, or vice versa.

Simplification workflow for hydraulically fractured reservoirs

Abstract Production from unconventional formations, such as shales, has significantly increased in recent years by stimulating large portions of a reservoir through the application of horizontal drilling and hydraulic fracturing. Although oil shales are heavily dependent on oil prices, production forecasts remain positive in the North-American region. Due to the complexity of hydraulically fractured tight formations, reservoir numerical simulation has become the standard tool to assess and predict production performance from these unconventional resources. Many of these unconventional fields are immense, consisting of multistage and multiwell projects, which results in impractical simulation run times. Hence, simplification of large-scale simulation models is now common both in the industry and academia. Typical simplified models such as the “single fracture” approach do not often capture the physics of large-scale projects which results in inaccurate results. In this paper we present a simple, yet rigorous workflow that generates simplified representative models in order to achieve low simulation run times while capturing physical phenomena which is fundamental for accurate calculations. The proposed workflow is based on consideration of representative portions of a large-scale model followed by post-process scaling to obtain desired full model results. The simplified models that result from the application of the proposed workflow for a single well and a multiwell case are compared to full-scale models and the “single fracture” model. Comparison of fluid rates and cumulative production show that accurate results are possible for simplified models if all important components for a particular case are taken into account. Finally, application of the workflow is shown for a heterogeneous field case where prediction studies can be carried out.

Production performance analysis during operation phase: A case study

Production performance analysis plays a significant role in supporting the decision-making process, for managers and engineers dealing with the challenges of the optimization procedure of a system delivery capacity. Operational conditions can influence the production performance of a system drastically, in a short or long term, by affecting the system configuration, reliability, maintainability, maintenance supportability, and functional capacity of its components. Moreover, these impacts can lead to increased business risks and uncertainties. Such a situation demands the successful application of tools and methodologies to minimize the total business risk through an accurate prediction of production performance, addressing the effects of operational conditions. However, there is a lack of practical methodologies, for production performance analysis of systems operating under the time-dependent operational conditions. Hence, the central thrust of this article is to develop a systematic methodology, for the production performance analysis of a system considering the time-dependent operational conditions. In the case study, the results show that the production performance of mining equipment is affected significantly by the operational conditions. These changes occur across the working shifts and due to any changes in the production plan of the mine. The result of the analyses shows that the critical items in the mine is the loader. Hence, in order to increase the production performance of the system, the optimization of the reliability or maintainability of the loader needs to be considered as a priority. Moreover, the wagon drill has a significant excess capacity, which means that, by adding more trucks to the system, the production performance of the system can be improved.

New water drive characteristic curves at ultra-high water cut stage

Abstract A function expression of the oil-water relative permeability ratio with normalized water saturation at high water saturation was proposed based on statistics of measured oil-water relative permeability data in oilfields. This expression fits the later section of conventional relative permeability ratio curve more accurately. Two new water drive characteristic curves at the ultra-high water cut stage (fw>90%) were derived by combining the new oil-water relative permeability ratio expression and reservoir engineering method. Then, the numerical simulation results of five-point well pattern and production data of Yangerzhuang Oilfield and Liuzan Oilfield were used to verify the adaptability of the new water drive characteristic curves. The results showed that the new water drive characteristic curves are more accurate than conventional water drive characteristic curves after A type and B type water drive curves rise, and can be used to predict production performance at ultra-high water cut stage, ultimate recovery efficiency and recoverable reserves.

Feature extraction on an intelligent polycrystalline diamond insert clock testing method and prediction of product performance

Increasing applications of polycrystalline diamond inserts in rock drilling is visibly seen as the discovery of new oil wells and tunnelling projects for metro lines are on a continuous rise around the world. As a result, the market consumption of polycrystalline diamond inserts is increasing severely. However, the sudden increased requirement of polycrystalline diamond inserts has also triggered a global competition as new players are increasing each day. The prevailing situation offers a dynamic challenge to the manufacturers to successfully stay in the business, and hence, enhancing product quality has become an essential requirement. In other words, to stay competitive and to remain ahead of the pack, it is critical to build up innovative testing capabilities of the polycrystalline diamond insert so as to pre-empty the undesirable functional characteristics of the polycrystalline diamond insert as well as to proactively engage the production floor for ensuring high product quality. This manuscript unveils a developed intelligent polycrystalline diamond insert testing platform that would link the failure characteristics of the polycrystalline diamond insert to the fracture mechanics through the study of process digitisation of the tool–work interface. An experimental set-up was developed, which incorporates a dynamometer, acoustic emission and accelerometer, for the digitisation of data signals in a feature extraction engine. The feature extraction engine in turn is used to monitor the failure of polycrystalline diamond cutting inserts during machining. The raw data fed through the feature extraction engine were used to identify the progression of failure in terms of flank wear or tool life for the polycrystalline diamond cutting inserts. The system comprises three key elements, which are (a) sensing and conditioning, (b) information extraction and (c) performance and failure analysis. The results of this experiment build the feature extraction engine that tracks the progression of flank wear in the polycrystalline diamond cutting inserts with reasonable accuracy. Furthermore, the break-in testing of a randomly selected insert from the production floor was applied to the feature extraction engine platform to predict the produce performance. This method also alerts the in-process manufacturing stages and enabled to considerably reduce the production scrap of polycrystalline diamond inserts.