Objectives/Scope A Multi-Phase Flow Meter (MPFM) performs Water Liquid Ratio (WLR) estimations using a dedicated sensor relying on one physical principle (e.g. electrical impedance). The accuracy of the WLR sensor might also be dependent on the flow properties. An approach based on Machine Learning techniques and multi-sensors data fusion has been implemented to enhance the reliability and accuracy of the WLR estimations in Multi Phase application using onboard sensor measurements of a MPFM. Methods, Procedures, Process In order to improve the estimations of multi-phase applications, we exploit the availability of historical data collected with heterogeneous sensors; the underlying idea of the proposed approach is to exploit such data with Machine Learning supervised techniques to provide accurate measures. In this work we compare modern supervised learning approaches like Random Forest, Gradient Boosting techniques and Kernel methods. The proposed methods have a relatively simple form that can be deployed also in embedded applications. Results, Observations, Conclusions In this work, we will show through extensive experiments that the proposed approach could improve the original estimations. The algorithms underlying the proposed approach have been trained using data collected at flow loops test facilities with different flow conditions. The best model has been chosen not only for its predictive performances, but also looking at the computational time needed to make a prediction and considering its robustness to outliers. As expected, depending on the dataset numerosity, the best performing model can change: we provide experimental results for various dataset sizes in order to help practitioners choose the best regression method depending on the available data numerosity. An additional considered aspect is the computational time of the various approaches, which may be a relevant characteristic to be evaluated before rolling out productive solutions. Novel/Additive Information To increase the accuracy of MPFM, a sensor fusion technique that benefits from the many measurements collected by the MPFM, has been developed. Many different models have been compared on: prediction performances, confidence interval, robustness to outliers, execution time. The resulting model provides enhanced estimations equipped with confidence intervals that can be used for prediction quality assessment and associated risk management.

Improving ESP performance has become one of the main challenges in gassy wells. Different methods and new technologies have been developed but most of them have high economic value. A new system has been created to prevent large amounts of gas flowing directly into the pump intake through the breaking of the gas slugs and the resolubilization (dispersion) of the free gas into the production liquid. The system contains an isolation section which allows to break gas slugs and pressurize that section forcing the gas to go in solution to be produced afterwards. The concept of the new technology is to manage the Rs (Gas in solution) with pressure, additionally the technology includes a vortex effect creator which will improve the gas dispersion iton the liquid associated and will separate the sand production. The ESP’s Downhole Regulator was designed based on each well conditions to maximize its efficiency. This paper summarizes the design and application of the new Vortex Regulator in more than 50 gassy wells completed in the Wolfcamp A, Wolfcamp B, Lower Spraberry, and Jo Mill C in the Permian basin. The performance evaluation was carried out by a constant monitoring of the sensor parameters through a certain period. During the evaluation period the ESPs in most of the wells were operating under stable conditions with minor shutdowns, no significant increases in the motor current, motor temperature, and vibration were observed.

With the gradually increasing applications of fiber-optic distributed temperature sensors (DTS) in unconventional resources exploitation, academic researchers have developed general theoretical models for forward temperature simulation and inverse flow rate profiling during and after stimulation workover. However, there have been no enough field applications for the established theoretical models and some practical issues still exist such as different completion scenarios are still lack of consideration in current models. This paper presents a DTS flow profiling case for a horizontal multi-stage fractured well in tight gas reservoirs with open-hole packer completion scenarios by applying a newly improved theoretical model. In this paper, for the modeling part, we start with the semi-analytical wellbore-fracture-reservoir coupled flow/thermal model but improve it to consider open-hole packer completion scenario. Compared with the conventional cased, cemented and perforated completion style, the fracture initiation points in open-hole stimulated well are more effected by near wellbore in-situ stress field. Therefore, the open-hole packer completion possibly forms a two-fold flow regime. The formation fluid firstly flows through the fracture into the open-hole annular space between formation and the packer liner, then flow along the annular space until meet the frac port on the production pipe. The two-fold flow regime results in double temperature drops due to Joule-Thompson cooling effect. The original theoretical model is improved by adding a simulation sub-region representing open-hole annular which helps to understand the flow and heat transfer inside it. With the improved mathematical model, DTS monitoring data during a three-rate production test in a horizontal multi-stage fractured well in Erdos Basin of China was simulated and analyzed. The improved model with open-hole packer completion was applied and then the gas flow profiling was accomplished.

Flowback rate transient analysis (RTA) is a practical tool for characterizing hydraulic fracture (HF) properties. However, the accuracy of the interpreted results from flowback RTA is challenged by the complexity in two-phase flow in the hydraulic fracture and matrix system. Accordingly, we present a new semianalytical method to characterize HF attributes and dynamics using multi-phase flowback data for tight and ultratight (shale) oil wells. The proposed method includes a two-phase diagnostic plot, a fracture RTA approach for straight-line analysis, and a matrix model capable of characterizing water and oil flow. The RTA approach is based on fracture infinite acting linear flow (IALF) and boundary dominated flow (BDF) solutions, which treats HF as an open tank with a variable production rate at the well and the contribution of water and oil from matrix within the distance of investigation (DOI). The pressure-dependent fluid and geomechanical properties, such as permeability and porosity, are considered in the pseudotime defined in fracture and matrix to reduce the nonlinearity of the system. We tested the accuracy of the proposed method against numerical results obtained from commercial software and verified its applicability by analyzing the flowback and long-term production data from a field example in Eagle Ford shale. The validation results confirm that our method can closely calculate water and oil influx from matrix as well as the average pressure and saturation in the HF and matrix DOI. The accurate estimation of the initial fracture permeability and pore volume demonstrates the applicability of the proposed method in quantifying HF properties from two-phase flowback data exhibiting fracture IALF and BDF regimes. The analysis results show that the estimated initial fracture pore volume shows more accuracy than initial fracture permeability due to the different calculation sources in the straight-line analysis. In short, the proposed method is, to our best knowledge, the first RTA approach incorporating the two-phase water and oil influx from matrix into the inverse analysis of fracture properties and dynamics using straight-line analysis, instead of history matching

An Aker BP operated oil field in the North Sea has occasionally experienced production flow instabilities in the production lines and risers. The oscillations in multiphase rates are kept within the process capacity limitation at the host installation typically by increasing backpressure (planned flaring is not allowed for on the Norwegian Continental Shelf). The heightened backpressure impacts the production potential of the field. The objective of the project described in this paper has been to develop and implement a new method for real-time production optimization providing an online assessment of slugging severity and suggested actions in order to mitigate slugging and increase production. The developed software tool has been validated using field data. A statistical approach based on the physical characteristics of the separator has been developed. A combination of transient multiphase flow simulations and data analysis has been employed in order to formulate the risk of exceeding separator constraints as a multidimensional function of the operational conditions. In order to generate a three-dimensional heat map of the risk related to the current state, operational data is continuously gathered from production sensors and transformed into pseudo-steady state values. A heat map is defined by a function where four relevant operational values can be selected. These values are: oil production rate, topside choke setting, gas lift rates and water cut. The software solution is run on a cloud infrastructure with an interactive web user interface. In a pilot program we have evaluated the ability of the stability advisor to continuously assess the severity of flow instabilities, identify measures to reduce the risk level and minimize associated production losses. The operator has identified valuable operational insights from the tool in a pilot program. The flow instabilities predicted by the model correlate well with observed data from the field. The tool is scalable to other fields with similar flow problems. Previous papers on slug flow prediction are in general conducted as offline study projects. There has been little success in making real-time scalable solutions available to continuous operations. This paper explains a method on how physical modelling of the flow system combined with statistical methods and access to real-time sensor data can provide a new approach for real-time slug flow prediction. The result demonstrates a scalable solution where output is presented in a format that can be applied by daily operations to act on and provide new and valuable production insights.

In recent years, well performance from tight reservoirs in the Delaware Basin has been improving due to enhanced completion practices, better reservoir targeting and improved well designs in the region. One of the key components to the enhanced completion practices has been the implementation of progressively longer laterals. The rate of increase in lateral lengths have slightly slowed in recent years, as operators approach the point of no additional value creation as the well costs supersede the production gained from longer wells. This paper presents a tool created to evaluate the performance and economics of a given well given different reservoir, fluid, well design and completion parameters. The tool is also a probabilistic model that can quantify the impact of input parameters that the user feels uncertain about. As a result, it can provide management teams with an approach to make capital decisions under uncertainty. The proposed methodology presented in this paper is repeatable for different tight rock formations across different basins. An example of the tool's capability is demonstrated in this paper using an asset profile typical of the Delaware Basin's Wolfcamp A.

Slug flows generate variable loads that excite pipelines, inducing oscillatory displacements and tensions of significant magnitude, raising concerns about the physical integrity of the pipe’s structure. The present paper presents a simulation model to compute non-uniform slugs, to provide a tool for the analysis of the dynamic behavior of horizontal pipelines in subsea petroleum production systems. This model was tested for a straight, horizontal, free span hanging pipeline supported at both ends. The development of the present methodology was based on a previous model of regular slugs. The present model takes into account the expansion of the gas bubble length along the pipeline, generated by the negative streamwise pressure gradient between the pipeline’s entrance and exit, resulting in a longitudinal sequence of non-uniform slugs. The model’s algorithm used to calculate the mass distribution in the slug flow is implemented in a subroutine of a pre-existent software, commonly known to simulate the mechanical behavior of pipelines under dynamic loads. The dynamic responses of a pipeline excited by non-uniform slugs – vertical displacement, bending moment and bending stress – were analyzed as a function of the gas expansion global rate, and were compared to the dynamic responses induced by a regular slug flow. It is concluded that the non-uniform slug distribution imposes a more complex excitation on the pipe, while the perfect regular slug flow induces an excitation with a single well-determined frequency. The difference between irregular and regular flows depends on the magnitude of the pressure gradient acting along the pipeline’s length.

This paper introduces pump-down diagnostics, an economical process in which cement sheath integrity, perforation cluster spacing and frac plug integrity can be assessed for every frac stage, potentially leading to improvements in stimulation, completion, cementing and drilling practices. It is based on analyzing wellbore pressure responses occurring at key segments of the wireline pump-down and perforating operation and correlating the results among multiple frac stages and wells in a field or play. A special requirement is that the frac ball (ball check) is inserted in the frac plug and pumped to seat prior to performing perforating operations. A complementary benefit of this process is that selectively establishing injectivity in the most distant perforation cluster can be used to establish inhibited HCl acid (wireline acid) coverage across all perforation intervals for uniform reduction in near-wellbore tortuosity. Reviews of pump-down diagnostics field cases from several unconventional plays provide the following insights. 1.) pump-down diagnostics are time efficient and economical, requiring about 15 minutes per frac stage, 2.) evaluating communication to the previous frac stage can serve as a key performance indicator for treatment control or cement sheath integrity, 3.) pump-down diagnostic results can be more reliable than cement bond log evaluation, 4.) stage isolation characteristics can be strongly affected by cluster spacing.

The purpose of this paper is to highlight the results of a comprehensive investigative study that quantifies the multiphase flow-related differences in multiphase hydrostatic pressure gradient, oil holdup and gas velocities as the gas injection depth is lowered from vertical to higher angles along the heel and into the lateral sections of horizontal wells. The results of this work enable a deeper understanding of gas slippage under gas lift operation at high angle sections of horizontal wells. When used for optimizing horizontal well liquids unloading, gas lift valves are placed as low in the well as operationally allowable. But what happens if gas lift is applied along the bend or lateral? To help address this important question, we first leverage the vast knowledge gained from the inclined multiphase flow literature. The scientific knowledge base for up/down inclined multiphase flows reveals why such behaviors in laterals are so complex, namely, the extreme slip effects that exist. In this work, we start with selecting published lab experiments in this area, and then simulate their flow behaviors using an advanced, cutting-edge analytical multiphase flow simulator. Next, we extend our validation to the field-scale using actual horizontal well gas lift field datasets sourced from different unconventional shale oil plays. With this detailed flow modeling substantiated, we then conduct the principal investigation of this work by quantifying the horizontal well gas lift performance at various representative inclinations (0, 30, 60, 88, 90 and 92 degrees from vertical) to better understand how changes in four major sensitivity variables, namely, diameter, gas injection rate, total liquids rate and water cut, impact the effectiveness of the gas lift process. Then, for each of these sensitivities and at each inclination, we analyze and compare the difference in value (value before gas lift - value after gas lift) of the multiphase hydrostatic pressure gradient, oil holdup, wellbore gas velocity and critical gas velocity. A new learning from this work is that the prior vertical well experience and basis for gas lift being more effective at deeper depths does not translate to horizontal wells. The experience-driven industry viewpoint that gas lift is unaffected by inclination is not supported by both controlled inclined flow loop lab data and horizontal well field data. From the multiphase view, gas lift optimization is governed by the slip behaviors and it is demonstrated in this work that the multiphase hydrostatic pressure gradient reduction will be much lower at horizontal well inclinations of greater than 45 degrees from vertical, meaning the gas lift technique becomes less effective at these higher inclinations deep in the heel and lateral regions. Our results show that in this latter scenario, most of the gas will slip past the liquids, and increasingly so at higher angles (the pipe acts as a separator at these higher angles) and the effectiveness of the gas lift significantly lowers as the flow starts to undergo slugging and other high-slip transitional flow patterns. This has a significant practical impact to operators trying to optimize end-of-tubing (EOT) placement in conjunction with the gas lift lowest valve placement. Summarily, the results from our detailed modeling are used to demonstrate what is and what is not possible in terms of liquids evacuation from horizontal wellbores using gas-assisted lift at up/down inclined angles - and specifically - how gas injection rates affect hydrostatic pressure gradients, oil holdups, wellbore gas velocities and critical unloading gas velocities along the bend and lateral.

The La Cira-Infantas (LCI) oilfield was discovered and put in production in 1918. After a traditional reservoir depletion stage, a water flood (WF) operation was started in 1958. Redevelopment began in 2005 as a joint venture between Ecopetrol and Occidental (Oxy) using a combination of workovers, infill drilling, WF optimization, and other IOR/EOR methods. The field has been redeveloped using an average 20 to 25 acres per WF pattern, which were either inverted 5-spot or 7-spot configurations. Since 2005, selective completion strings were installed with side pocket mandrels controlling the vertical distribution and volume of water injected with each mandrel covering a group of sand layers. The selective completion was successfully implemented, and provided a significant boost in oil production. The field has multiple opportunities to increase oil production. Before performing these solutions, it was important to understand the producer-injector connectivity across the entire field. The capacitance resistance model (CRM) provided some insights on the interwell connectivity within the reservoir between injectors and producers, however it is difficult to correlate the CRM simulation results with multiple geological interpretations and reservoir characterizations using geostatistics. This paper presents a WF surveillance program with a focus on incremental oil recoveries from multiple stacked-sands. The injection and production profiles were very useful in improving WF conformance. The water injection profile was measured with a rigless tracer string. The production profile was initially estimated using petrophysical properties and fractional flow curves due to the difficulty of running a production logging tool (PLT) from every pumping well in complex multilayer reservoirs. It was important to validate the production profile with a couple of PLT pilot wells. In these pilot wells, we employed a Y-tool for a connection with the electric submersible pump (ESP) on one side; and the other side of the Y-tool served as a pass through for the PLT. The production and injection profiles provided insights for injector-producer well correlations between productive sand layers. Based on the well data, reservoir simulation models were created and have added value to our reservoir surveillance program, significantly increasing oil production, WF sweep efficiencies, and incremental oil recoveries in the mature LCI WF oil field.

This study demonstrates the application of an interpretable (or explainable) machine learning workflow using surface drilling data to identify fracable, brittle and productive rock intervals along horizontal laterals in the Marcellus shale. The results are supported by a thorough model-agnostic interpretation of the input-output relationships to make the model explainable to users. The methodology described here can easily be generalized to real-time processing of surface drilling data for optimal landing of laterals, placing of fracture stages, optimizing production and minimizing frac hits. In practice, this information is rarely available in real-time and requires tedious and time-consuming processing of logs (including image logs), core, microseismic data and fiber optic sensor data to provide post-job validation of frac- and well-placement. Post-completion analyses are generally too late for corrective action leading to wells with a low probability of success and increasing risk of frac hits. Our workflow involves identifying geomechanical facies from core- and well-log data. We verify that the geomechanical facies derived using core- and well-log data have characteristically different brittleness, fracability and production characteristics. We test and investigate several different supervised classifiers to relate surface drilling data to the geomechanical facies. The data was divided into training and test datasets, with supervised classification techniques being able to accurately predict the geomechanical facies with 75% accuracy on the test dataset. The clusters predicted on test well (unseen data) were qualitatively verified using the microseismic interpretation. The use of Shapley Additive Explanations (SHAP) helps explain the predictive models, rank the importance of various inputs in the prediction of the facies and provides both local and global sensitivities. Our study demonstrates that pre-existing natural fracture networks control both the hydraulic fracture geometry as wells as the production. Natural fractures promote the formation of complex fracture networks with shorter half-lengths which increase well productivity while minimizing frac hits and neighboring well interactions. The natural fracture network is itself controlled by the geomechanical properties of the rock. The ability of the surface drilling data to reliably predict the geomechanical rock facies provides a powerful tool for real-time optimization of wellbore trajectory and completions.

Electrical submersible pumps (ESP) oil well production often requires handling large amounts of free gas, leading to numerous ESP trips, which limits drawdown. To maximize production and eliminate downtime, a technique was developed to distinguish between three possible different causes i.e. gas locking, ESP flowrate oscillations, and dynamic instability and thereby improve design and operating procedures. The theory is illustrated with case studies and real time data. The main objective was to determine the cause of observed well instability and understand the interaction between the pump and the remainder of the wellbore. In addition to using classical steady-state nodal analysis, the analysis used downhole flowrate simulations to capture ESP transient oscillations. Furthermore, system dynamic stability analysis identified when and why the interaction between the pump and the wellbore results in flowrate and pressure instabilities, which can lead to pump mechanical failure. Combining holistic well analysis with a review of case studies led to identifying several types of gas-induced problems, root causes, and solutions. For each type, diagnostic techniques were developed in addition to design and operational recommendations. Interestingly, in some cases, where traditional diagnostics would have pointed to gas locking in the pump as a root cause, the new analysis demonstrated that well slug flow regime dominated the well and ESP behaviour. A key conclusion from the analysis was that real-time measurement of intake, discharge, and wellhead pressures is necessary to correctly distinguish between pump gas lock, well flow regime issues (e.g. slugging) and system instability. Furthermore, real-time downhole measurement of transient flow rate through the pump is indispensable feedback to operators for managing wellhead pressure and pump frequency with the aim of maximizing drawdown, stabilizing the well, and extending the ESP run life. A key finding is that irrespective of the cause, it is always best to operate the ESP at rates greater that the best efficiency point, which usually requires over staging the design. Finally, the case studies presented in this paper illustrate the importance of capturing the relative slopes of the pump and well system curves as well as how they change with time. Combining new models with real-time data improves the accuracy of diagnostics and therefore enables increasing the GVF that ESP wells can handle and thereby maximizing production by either eliminating trips and/or maximizing drawdown.

The current scenario of many Pre-salt wells considers high rate stimulation process after a long-term shut-in due to temporary abandonment. Thus, the wellbore is at geothermal temperature in the beginning of an acidizing operation. In an ultra-deepwater environment, like the Pre-salt cluster, the temperature reaching the wellhead during acidification is near 4 °C. Numerical simulations have shown that the wellbore cooling down during short transient injection operation can lead to well integrity failure collapsing the intermediate casing. The approach commonly employed in the industry considers just steady state injection operations which are not enough to describe what is happening in the field and are also not sufficient to support a suitable casing design. The industry must put efforts to develop and consolidate a methodology based on transient thermal analysis to deal with thermal shock events in the well, as proposed in this paper. This paper aims to show the main findings of Petrobras wellbore design team to deal with reverse APB during well cooling down operation. In order to mitigate the decrease in pressure, unusual fluids were assessed as packer fluids. In addition, a comprehensive analysis was developed and proposed to deal with transient thermal phenomena in commercial wellbore thermal-structural simulators once some of the important identified loads are currently neglected by O&G industry standards. Results have shown that several alternative packer fluids might reduce or prevent casing failure due to fluid thermal isolation and/or shrinkage. Several case studies that led to loads under the collapse safety factor before, are now meeting appropriate values. Also, it was demonstrated the key parameters that affect wellbore transient analysis. Overall, predicting reverse APB, especially during short transient wellbore cooling down must be faced carefully.

Pore-scale images and core-scale imbibition experiments suggest that hydrocarbon and water tend to flow through their own pore network, referred to as "stratified flow". The objective of this paper is to investigate the occurrence of these phenomena at reservoir scale by analyzing flowback and post-flowback production data. Understanding multiphase flow regimes is the first step for selecting proper relative permeability curves and developing representative multiphase rate-transient models. Another objective of this paper is to investigate the harmonic decline (HD) behavior of water-oil ratio (WOR) versus cumulative water production volume and how it could be employed to compare load recovery performance of different wells. We analyzed flowback and post-flowback production data of six multi-fractured horizontal oil wells completed in Eagleford Formation. The proposed data-driven methodology involves using multiphase diagnostic plots of rate-normalized pressure, rate decline, and WOR. We applied this methodology to i) investigate the relationship between water and hydrocarbon at early production time; ii) model WOR with respect to cumulative water production; and iii) evaluate how fracturing/completion design parameters affect well performance. The results show three key findings: i) During early production time, we observe independent flow regimes (stratified flow) of water and oil indicating their production under different drive mechanisms. Water is produced from an apparently closed tank comprising induced fractures and the surrounding stimulated matrix, and oil is produced independently at a significantly lower rate due to oil influx from matrix into fractures. ii) After jet-pump installation, we observe coupled flow of water and oil indicating their production under similar drive mechanisms provided by the pump. iii) Semi-log plot of WOR versus cumulative water production shows HD trend that is relatively less sensitive to operational changes compared to water rate-decline plots.

Oil and gas gathering systems can experience flow instabilities characterized by cyclic pressure variations and liquid or free water surges out of the flowlines that typically cause liquid or gas handling problems in receiving facilities and dynamic external loads in elbows and T-junctions. This study describes a new mechanism of instability of gas-liquid flow in a well-flowline-receiving facility system referred to in other industrial applications as the density or liquid holdup wave oscillations (DWO). Unlike instability phenomena related to hydrodynamic slugs, terrain-induced slugs or riser-induced severe slugging, this type of instability is a result of multiple feedback effects between the flow rate, pressure drop, and liquid inventory (the total volume) in the flowline. The specific DWO instability mechanism proposed in the present study is related to generation and propagation of a liquid holdup wave with a large amplitude and wavelength several times greater than the length of a hydrodynamic or terrain-induced liquid slug. A new stability criterion to predict the DWO onset is proposed based on Ultra-High Definition (UHD) simulations of three-phase gas-oil-water flow to accurately predict the liquid inventory. Field data showing a transition from unstable to stable operation in an offshore oil production system are presented. The system is used to transport produced fluids from a satellite platform with naturally flowing and gas-lifted wells to a central platform with processing facilities, via a 30-in. diameter flowline. The stability criterion was used to identify the root cause of large-amplitude oscillations of pressure and flow rate in the flowline. Thus, proposed dynamic two-phase flow instability mechanism and criterion are a cost-effective and practical method for predicting instability onset conditions and developing mitigation strategies in existing and new-built production facilities.

Improper hole cleaning is a major cause of non-productive time (NPT) in drilling. Current hole cleaning practices are mostly based on experience, rules of thumb and simplistic calculations. Hence, they are not reliable and do not work as expected in all scenarios. There is the need for a robust, fast, and accurate approach to simulate cuttings transport, and provide reliable and useful estimations of the hole conditions in real-time. In this paper, a transient cuttings transport model is presented for real-time hole cleaning simulations. The model solves the transient conservation equations using a drift-flux modeling approach, which is applied to describe the multiphase flow of cuttings and fluid in the wellbore. The model uses experimentally derived equations that account for the effects of pump rate, pipe rotation, eccentricity, fluid rheology, inclination, etc. on cuttings transport. A fast numerical solver is used to enable real-time simulations, while providing numerical stability that is crucial to maintain the modeling convergence under area discontinuities. Using small time-steps, the model captures pressure wave behavior, which is necessary for simulating managed pressure drilling (MPD) operations. Pressure-dependent mud density, non-Newtonian viscosity, and cuttings slip velocity models are used to estimate downhole parameters such as pressure, cuttings concentration, bed height, drilling fluid and cuttings velocities, etc. The model can provide a drilling crew with accessible real-time simulation results on the rig for monitoring the hole cleaning operation and preventing problems from happening. Case studies are performed based on field experiments to analyze the effectiveness of the developed model on avoiding operational problems such as pack-off and stuck pipe. Results show that by monitoring the real-time cuttings concentration and bed height along the wellbore, the developed model can detect improper hole cleaning conditions and provide optimum drilling parameters to resolve problems, thereby minimizing NPT. The robust numerical scheme allows for simulations that are several times faster than the real-time operation on a standard desktop PC, providing the crew with enough time to take preventive actions. Clean-up cycles can also be simulated by the model to calculate and optimize the required parameters for optimum hole cleaning results. Required clean-up times are calculated for the field cases to ensure that cuttings are effectively removed from the wellbore before pulling out of hole and running casing. Moreover, MPD operations can be simulated using the model that consider the effects of cuttings concentration and bed blockage on the pressure profile. The developed model can provide valuable real-time information on downhole conditions to the drilling crew during the drilling process and give adequate time to the crew to take timely corrective action if necessary. Moreover, the model can simulate the planned drilling process and calculate optimum drilling parameters to avoid hole cleaning problems.

One of the continuing puzzle pieces for all unconventional plays is drawdown (DD) technique for optimal Return on Investment (ROI). A solid approach to determine this valuable piece of information has yet to be found, as many operators are reluctant to reveal the production, pressure, and completion data required. Among multiple parameters, various completion and spacing parameters add to the complexity of the problem. This paper aims to determine which drawdown strategy leads to the highest return in the Anadarko Basin,, specifically evaluating the Woodford and Mayes formation. Several drawdown techniques were used within the Anadarko Basin in conjunction with different completion techniques. Private production and completion data were analyzed and combined with well log analysis in conjunction with data analytics tools. This case study explores a new strategy to drawdown producing wells within the Anadarko basin to achieve ultimate ROI. We perform data analytics utilizing analytics (scatterplot smoothing) to develop a relationship between two dependent variables Estimated Ultimate Recovery (EUR) and Initial Production (IP) for 180 days of Oil vs. drawdown. We present a model that evaluates horizontal well production based on drawdown parameters. Key data were estimated using reservoir and production parameters. The data led to determination of the most optimal drawdown technique for different reservoirs within the Anadarko Basin. This result may help professionals fully understand the Anadarko Basin. By use of these optimal parameters, we hope to completely understand the best way to drawdown wells when they are drilled simultaneously. Our findings and workflow within the Woodford and Mayes formations may be applied to various plays and formations across the unconventional play spectrum. Optimal drawdown techniques in unconventional reservoirs could add billions of dollars in revenue to a company's portfolio and increase rate of return dramatically, as well as offer a new understanding of the reservoirs in which we are dealing with.

During hydraulic fracturing of low to moderate (0.1 – 50 md) permeability reservoirs using crosslinked gel fluids, the final proppant stage displacement is designed to leave some volume of proppant slurry above the perforated interval. This practice of underflushing is based on a paradigm that considers the overdisplacement of proppant past perforations to be a major risk to well productivity. The theory behind this paradigm is investigated and finds that it relies on several physically unrealistic assumptions. Numerical simulations were performed to understand the impact of a fracture overflush on well productivity. A new methodology was developed for overflushing fractures that enables significant cost/time savings without impacting well productivity. A multi-well field trial in a 2-20 md reservoir was conducted andcompared well performance from overflushed crosslinked gel fractures to underflushed fractures. Some of the trial results have been reported by the authors ( Chaplygin et. al. (2019) ) and are further updated/analyzed in this work. The analysis confirmed that the managed overflush fractures have equivalent performance to underflushed fractures. The analysis also confirmed multiple benefits from the managed overflush wells including reductions in completion costs/time and an improved HSSE risk profile. The results challenge the validity of this decades old paradigm.

Distributed temperature sensing (DTS) is an enabling technology for fracture diagnosis and multiphase flow measurement in unconventional areas. DTS data analysis includes the warm-back stage and production stage analysis. The warm-back stage analysis can provide the slurry flow and proppant allocation. The production stage analysis can be applied to flow profiling and fracture characterization. The objective of our DTS data analysis approach is to provide an integrated quantitative diagnosis of effectiveness of staged fracturing, and hydraulic and natural fractures with the full-physics model, which will benefit the fracturing operation design and decision-making process in the unconventional reservoir. In this work, we developed a comprehensive numerical forward model for DTS data analysis. Our model includes reservoir and wellbore models. Also, the flow and thermal models are fully coupled. A thermal embedded discrete fracture model (Thermal EDFM) is developed to handle the thermal modeling of complex fracture networks. The DTS analysis with our model provides a high-resolution solution since the fracture diagnosis and flow profiling are performed for each fracture. With this analysis, we obtain a deeper understanding of the effectiveness of the field hydraulic fracturing operation. Although numerous simulators are developed for DTS data analysis, relatively few existing models can handle the full-physics such as complex fracture geometry and multiphase flow. Our inverse model provides an improved DTS data match result. Our model is more rigorous than the prior models to simulate and match the field DTS data.

The most common stimulation technique for shale production is multistage hydraulic fracturing. Estimating fracture geometry is a focal parameter to judge the fracture operation and predict the well performance. Different direct and indirect techniques can be used for fracture diagnostics to estimates fracture geometries. The current study combines fracture measurements and pressure transient analysis to estimate fracture surface area on each stage and to estimate production as a pseudo production log. The numbers and kinds of fractures were calculated as a function of treating pressures, injection rates, proppant concentrations, and formation properties to compute fracture surface area (FSA). Pressure transient analyses were then conducted with the leak-off data upon completion of each frac stage to estimate the producing surface (PSA). The fall-off data was processed first to remove the noise and water hammering effects. The PTA diagnostic plots were used to define the flow regime and the data were matched with an analytical model to calculate producing surface area. Tensile and shear fractures are both created during the injection of frac fluids. Shear fractures are caused by movement in already existing natural (fluid expulsion) fractures found in all shale source rocks. Shear fractures form a pressure below the minimum horizontal stress. These shear fractures take advantage of the rock fabric and develop higher surface area than tensile fractures for the same given volumes of water and sand. FSA is a measure of permeability enhanced area due to hydraulic fracturing. Producing surface area is the resulting effective flow areaconnected to the wellbore. Diagnostic plots showed a linear and radial flow regime depending on the formation and the completion design. Good correlations were found between PSA and FSA results. In general, higher FSA produces higher PSA. In cases where producing surface area was higher than expected from fracture surface area, communication was found with offset wells. When FSA higher than PSA were found, it was usually caused by increased stress from too close offset wells. Combining FSA and PSA measurements provides forecasts of production for each stage and helps to optimize well spacing at the end of each frac stage.