Abstract This paper discusses a new technology that helps to identify and differentiate multiple downhole well integrity events - tubing leaks, casing leaks, flow behind casing and overburden integrity, using unique algorithmic pattern recognition capability based on acoustic measurements from Distributed Acoustic Sensing (DAS) data. Here, we demonstrate application of this technology to identify flow behind casing and effectively build remediation strategies for Plug and Abandonment (P&A) of one of the wells in a BP operated field. Applying DAS for tubing leak detection has been discussed in prior publications. The approach has however, relied on simple data processing methods ‘listening’ for zones of increased noise when wells are shut in. In this paper, we discuss results from the application of a novel real time pattern recognition based approach to processing data from DAS that: Denoises data to decouple fluid movement ‘signals’ from background noise Uses signature recognition to constructs fluid ‘flow logs’ across the entire length of the well bore every second; Displays evolution of the fluid noise through depth and time The technology has been deployed across several assets for identifying well integrity events through different stages of well life – starting from drilling, production through to abandonment. In this paper, we demonstrate the application of the new capability for identifying flow behind multiple casing strings on one of the BP operated wells. The system was deployed to identify and pattern the evolution of fluid movement noise behind multiple casing strings through time and depth which was then used in conjunction with a tailored operational workflow to inform effective remediation strategies for plug and abandonment of the well. The fluid flow logs generated were used to conclude on the source of flow, flow propagation and pathway and facilitated an informed decision on extending the well’s first lateral barrier into the formation and adjustment of the position of the planned second barrier. The results showed the effectiveness of the capability in the field and demonstrated its unparalleled value for the operator, allowing for well abandonment. The technology offers a new method of acoustic data processing on DAS that extracts valuable and often hidden insights to identify the source of fluid flow and flow pathways, providing an ability of capturing events behind multiple casing strings – all fundamental challenges that the industry has been looking to solve for several decades.

Abstract In producing oil and gas wells, two-phase flow of gas and liquid is inevitable. Gas density is lighter than liquid density, as a result, gas travels faster than liquid, leaving the liquid phase to build up in pipe segments. The amount of liquid occupying each pipe segment varies. This phenomenon is called liquid holdup, which is defined as the ratio of the liquid volume in a pipe element to the volume of the pipe element. Liquid holdup presents challenges in calculating mixture physical properties and two-phase flow pressure drop. Estimating liquid holdup is the first step to investigate production wells problems. Early detection and identification of liquid holdup ( H L ) in oil and gas wells is needed to reduce the maintenance downtime and thus increase production. This is significantly crucial in designing oil and gas facilities. Consequently, many studies on predicting liquid holdup have been carried out in the past, considering different flow conditions, resulting in a large number of empirical correlations with various degrees of accuracy. Machine learning approaches in predicting liquid holdup in multiphase flows have been recently studied to improve the prediction accuracy compared to the existing empirical correlations. However, these approaches ignored the heuristic feature importance of the input parameters to the predicted H L values. In our study, a machine learning predictive model, boosted decision tree regression (BDTR), is trained, tested and evaluated in predicating H L in multiphase flows in oil and gas wells. Decision trees are considered as non-parametric machine learning models. The datasets used in training and testing the predictive model are experimental and they were collected from literature (111 data-points). Air-kerosene and air-water mixtures were used in obtaining the 111 experimental data-points. Results show that, the proposed BDTR model outperforms the best empirical correlations and the fuzzy logic model used in estimating H L in gas-liquid multiphase flows. For the built model, the most important input feature in estimating H L is the superficial gas velocity ( V sg ). The empirical correlations developed in the past for identifying H L in the multiphase flow phenomenon can only be applied under certain flow conditions by which they were originally developed but this machine learning model does not suffer from this limitation. To the best of our knowledge, the present study is the first work that shows how the decision forest regression predictive models can accurately predict H L . Using the BDTR model with its interpretable representation, one can clearly determine the heuristic feature importance of the input features used in building the model. Heuristic feature importance can help in having a better insight of the issues associated with the H L studies, such as the liquid loading phenomenon.

Abstract In reservoirs management, sometimes it becomes difficult to identify which injector is supporting which producer(s) by graphs visual inspection. Available built-in correlations like Pearson –within common spreadsheets-, only valid for strictly monotonic (only increasing or decreasing) trends. A situation that is nearly impossible to see in real production/ injection trends. To resolve this issue, we developed a correlative tool in spreadsheet based on Spearman's correlation to assess communication degree between wells using production/ injection data. The method essentially implemented then non-parametric Spearman's correlation - valid with non-monotonic trends- and used visual basic application (VBA) coding language to provide easy to use worksheet. The input data needed are: production/injection data of the well(s), with any desired parameter like oil rate, water rate, GOR or water cut. After running the code, the outputs are numbers between −1 and 1 reflecting correlation coefficients between WI-OPs production parameters or OP-OP parameters. Zero or close to zero means no correlation, number close to 1 mean very strong proportional correlation and a number close to −1 reflects inversely proportional correlation. The tool was built successfully and enabled quick injection/production correlation between one injector and several producers at once using available production data. Also, it can run production/injection correlations between one producer and several injectors. Currently, it can measures correlation between one injector with up to 32 producers, or with 32 different parameters of several producers like water cut, gas oil ratio (GOR), oil rate, water injection rate, and water production rate. Moreover, it can correlate between producer-producer to check for interference. The code was found to be fast. Results from this tool were compared to results obtained from streamlines models and tracer injection in two different fields, one was naturally fractured carbonate and the other was sandstone. Evaluation of the tool ability to find true interactions between wells was achieved by comparing results of correlations coefficient with underground flowing tracers and streamline simulations. Some agreement was found between, streamline models, tracer surveys and Spearman correlation in well known areas to have well-well communication. Some limitiations were identified. Nevertheless, the tool can be used as a quick scanning tool for communication between wells. This tool provides an addition to the inventory of existing investigative methods like tracers, streamlines, and diagnostic plots and gives more weight to results from these techniques on identifying which wells in communication. The tool is easy to build, simple to use and fast to run. The tool might help reservoir management teams to better manage reservoirs, and free more time for engineers to improve production and increase oil gain.

Abstract This paper will portray the development and deployment of remote-activated sliding sleeve devices commissioned for use in a two-stage completion North Sea project. The sliding sleeves are required within the lower completion to provide access to the reservoir, protection to a control line and act as part of the fluid-loss envelope. Remote activation technology has been implemented to the sleeve designs to improve efficiency and introduce operational flexibility. Three variants of sleeves were designed and deployed to facilitate well objectives. The first variant is run-in-hole (RIH) Open to provide a circulation path and subsequently closed post displacement activities. The second variant is RIH Closed and is distributed across the reservoir. These sleeves are remotely opened post Xmas tree installation and provide the tubing/annulus communication for production or injection. The third variant is again RIH Closed, but this is a purely mechanical sleeve to allow further access to compartments or different reservoir units later in the well's life. A variant of open-hole anchor with bypass capability was also developed and tested. Remote-activated sliding sleeves were prototyped and qualified to API 19AC. In addition to the standard requirements of API 19AC, open/close cycles were also performed with lost circulation material-laden (LCM) fluid along with low hydrostatic pressure function testing. This latter testing is to allow for sequential functioning without having to shut in or choke back the well, instead functioning while the well is flowing or even under full operational drawdown. Three wells have been completed to date, two producers and one injector. The RIH Open sleeves have successfully acted as a replacement to a traditional fluid loss valve and the RIH Closed sleeves have allowed zonal isolation, selective water shut-off and reservoir management. The use of open-hole anchors has also been standardised, in producers to support future stimulation operations and in injectors to combat thermal contraction. Across all three wells the RIH Open sleeves have all been actuated successfully via Radio Frequency Identification (RFID) tag carrier or timer and the RIH Closed via pressure sequence and / or timer. The second producer also saw the first implementation of the staged clean-up functionality with sleeves opening at four different intervals over a period of 17 days.

Abstract The thrust to measure multiphase flow in oil wells is driven by the need to optimize well/reservoir management. This has driven R&D to develop an accurate and cost effective multiphase flow meter. In ESP-lifted wells, the continuous measurement of the flow rate and other attributes are critically important to optimize the performance of the pump, and consequently prolong its run life. Despite the surge of technologies and subsequent R&D to develop surface and subsurface tools to measure/infer the flow rate through the pump, the industry has not yet developed a viable meter that is to be installed in each well. The industry attempted to utilize the readily available data from the application of digitization, to infer flow rate, but it is not fully leveraged to serve that purpose and substitute surface meters. This paper presents new solutions that augment multiple attributes (electrical, hydraulic) and schemes (analytical, & numerical) to estimate multiphase flow estimations in ESP-lifted wells. The solution is a semi-analytical solution with regression analysis that augments different methods, to improve the reliability of calculation and help understand the wellbore phenomena to calibrate pump curves and pressure traverse models and crosscheck results for multiphase flow. The proposed solutions reduce inherent uncertainties in fluid properties and fluid flow characterization. The solutions present a novel approach of data analytics, of simultaneously calculating multiple attributes to cross check results and improve accuracy. In addition, it could be utilized to calibrate some model of calculations used and assesses reliability of some systems that are monitored. It leverages the readily available data of monitoring ESP health for measurement calculation. Additionally, it presents some ideas of developing the future downhole virtual and/or physical meter. Some ideas are presented in the paper. Actual data is presented in this paper utilizing the proposed solutions. The solution showed good consistency among the used methods and great match with conventional reference measurement, which support the potential of application in the field. This set the stage to develop a downhole meter, to be used for better accuracy with the presented solutions. A proposal of the downhole meter and its connectivity the proposed solution is presented. Artificial intelligence tools could be considered for future research utilizing to fine-tune the calculated estimations.

Abstract In the subject reservoir, geological features (high perm streaks and fractures) are the key performance drivers that affect injected water movement behavior. However the horizontal and vertical distribution of these features have high uncertainties and it is very challenging to accurately capture these features and map into model. Here we developed one workflow to capture these features by integrating different sources of solid data, from core, open-hole resistivity log, PLT, well testing, production and surveillance data, etc. This reservoir has been on production for decades and plenty of static and dynamic data were acquired for the whole field. Among those data, conventional core analysis (CCAL), log derived k-PHIE regression, and well testing will measure reservoir permeability values, which could give guidance to the areal distribution of high perm and low perm regions. Afterwards, the difference between well test interpreted perm and CCAL measured perm could give some indication of some geological features (HKS, fractures, etc.) existing or not. Furthermore, these geological features could be further confirmed by the dynamic data, such as open-hole resistivity logs, PLT, and well production performance data, etc. After confirmation, those preliminary geological features will be mapped into static and simulation models, and the seamless geo-engineering loop of history match process will proceed until the final history match stage without compromising geologic plausibility and consistency. Going through the above integration workflow, the history match process was completed and the final history matched simulation model gives very promising water saturation match quality in both horizontal and vertical directions. In the horizontal direction, ∼90% of the producers get water cut match (trend and magnitude, dWC<5%), and also for recent drilled long horizontal producers (maximum reservoir contact (MRC) wells), model production profiles and water entry points along the laterals have good alignment with PLT and open-hole resistivity log data. In the vertical direction, model water saturation profiles have good alignment with open-hole resistivity log trend for hundreds of wells (∼90% matched). PLT and WFL also have very good match quality. In general this simulation model could reproduce water movement very well in three dimensions using this new integration workflow, with much improvement compared to current the model. It gives higher confidence in the model predictive capacity, and the future field development plan will be studied using this New Generation Model Based on this integrated approach, a more plausible and consistent set of geological features are mapped and thus achieve promising history match quality of water movement with minimum local modifications, and thus enhance the model predictive capacity and provide better support of the life cycle field development.

Abstract Multiphase flowrate measurements play an important role during the reservoir characterization and production optimization phase of reservoir management. Accurate multiphase flow rate measurement is an indispensable tool for production optimization from oil and gas fields. One of the industry's accepted solutions is the use of multiphase flow meters, which are expensive, have a limited operational envelope, and are exposed to erosion and failures. This can limit the applicability of physical metering devices due to frequent calibration, transportation issues, space, safety, security, and possible high costs. Virtual flow metering (VFM) is a method for estimating oil, gas and water flowrates produced from wells without measuring them directly. The method uses data available from the field, such as downhole pressure and temperature measurements as well as a choke position and ESP operational parameters, to estimate the flowrates by implementing hydrodynamic multiphase models, measurement data, and a reconciliation algorithm. In this paper, an overview of the conventional multiphase flow metering solutions is presented, which is followed by application of some advanced artificial intelligence and data analytics techniques for a specific case of multiphase production monitoring in a highly dynamic wellbore. The considered case refers to a typical scenario, where the measurements of oil, gas, and water flow rates are obtained in real time using a topside multiphase flow meter. Alternatively, the values of these multiphase rates are estimated using a data-driven dynamic flow model obtained using a dynamic mode decomposition technique. The results obtained with this method are compared with another VFM approach, where the rates are obtained using deep LSTM neural network.

Abstract Recent development of horizontal well completions and stimulation methods enhanced the development of conventional and unconventional resources. Multistage fracturing allowed oil and gas operators to stimulate long laterals in continuous and efficient operations that increase the reservoir contact, thus increasing the recovery of oil and gas. Oil and gas operators work to improve the efficiency of multistage fracturing treatments by developing and integrating enabler hardware, processes and chemical technologies to enhance the fracturing operations and reduce cost. This paper reviews and discusses the different types of horizontal wells with multistage fracturing completions and stimulation techniques including plug-and-perf, abrasive jetting, just-in-time perforation, sliding sleeve systems, coiled-tubing conveyed fracturing systems and annular isolation methods. The efficiency of the multistage fracturing treatments depends on multiple factors comprising the operational time and cost associated with different type of completions such as plugs and sleeves, different intervention operations such as wireline or coiled-tubing and different stage distribution and pumping designs. Combination of multiple multistage fracturing methods resulted in hybrid cost-effective treatments. In addition, multistage fracturing fluids diversions contribute significantly to the stimulation efficiency. Different types of diversion methods are discussed for each stimulation system. This paper provides a comprehensive summary of the operational practices, fracturing methods, and different multistage fracturing completions in horizontal wells while emphasizing on the recent advancements available in the market. The ability to develop an efficient and effective multistage fracturing operation is based on understanding the reservoir requirements, and identifying logistical and resource challenges at the geological location where the operation is taking place. The developed solutions would be an integration of currently available process, with proper completions, materials and development of innovative enabler technologies to accomplish optimum procedures. In recent years, several enabler technologies were developed to address the challenges within the existing multistage fracturing operations. The electronic monobore sliding sleeve was developed to address the limitation caused by small ball seat (baffle) in ball actuated sliding sleeve completions. Plug-and-perf operation was enhanced by applying the Just-In Time Perforation (JITP) method by developing a new perforation gun assembly that cuts operation time. Development of autonomous completion elements with the ability to navigate and self-destruct after accomplishing the job helped to reduce the number of trips into the well that greatly affected the operation efficiency. Completion elements and diverters built from dissolvable materials eliminated the drill-out and cleanout operations, which reflect positively on the efficiency of the fracturing process. Reviewing current advancements of multistage fracturing completions and treatments can pave the way for further operation optimization and cost reduction.

Abstract Fiber Optic Liquid Leakage Detection (FOLLD) project has permitted of assessing on the DTS (Distributed Temperature Sensing), the DSTS (Distributed Strain and temperature Sensing) and the DAS (Distributed Acoustic Sensing) capabilities, combined with a Standard Telecom Fiber Optic Cable (FOC), for detecting small pressurized (20 barg) and pre-heated (50 °C) liquid (water) leakages on a buried dummy pipeline. DTS/DSTS real time results demonstrated that the soil disruption, the soil and external environmental temperature variation had an influence on leakage detection results robustness. Consequently, only the first three (3) trials out of the ten (10) trials provide some comprehensive results. Real time results shown that two (2) out of three (3) DSTS devices were able to detect a leakage up to twenty (20) km with a detection success rate of 67% in the position P1 or P2 or P3. One (1) out of two (2) DTS device detects up to twenty (20) km with a detection success rate that depends on the fiber optic position (67% for P2 or P3 and 33% for P1). Only one (1) DSTS shows a detection success rate up to fourty (40) km with a detection success rate of 67% in the position P1 or P2 or P3. DTS/DSTS real time results highlight that 100% successful detection rate can be reached up to twenty (20) km with several fiber optic cables in the position: P1/P2 or P1/P3 or P1/P2/P3. For DAS systems, the real time results shown that it was not possible to distinguish a leakage "noise" from other surrounding noise. This was especially due to the water pump noise, which was always occurring simultaneously with the leakage. Only a post processing treatment provide the leakage detection using a DAS technology. Post treatment DTS/DSTS and DAS detection success rate are better than the real time results. This highlight the potential of both technologies. All DTS/DSTS and DAS testing results demonstrated that the detection success rate are Supplier's dependent.

Abstract This paper will describe pre and post workover well diagnostic and the successful water shut-off that has resulted. It also talks about the post workover survey. The well was recently completed to a new targeted reservoir and suffered from high water cut (80%) at the start of production. Proper diagnostics identified the source of water and helped in planning a successful remedial job. After water shut off the water cut dropped to zero. Post workover evaluation confirmed production from the targeted interval. Comprehensive diagnostics are crucial to designing a proper remedial job. A conventional PLT survey will describe the flow characteristics and parameters inside the wellbore only. During the job under consideration, two additional services were deployed; the Spectral Noise Logging and the High Precision Temperature sensing. Their combination with the PLT allows for the assessment of behind casing flow and the identification of active streaks of the formation. The quantification of flow rate behind casing is also achieved by modelling the temperature response from the high precision sensor. The first survey was conducted with the conventional PLT to identify the source of water. Subsequently, a high precision temperature and spectral noise log were recorded under flowing, transient, and shut-in conditions. A crossflow behind casing from the upper unperforated intervals was identified. The main liquid production is coming from the water-bearing formation that is located 15 ft above the targeted reservoir. The cement evaluation surveys that were run previously confirmed the presence of a cement channel above of the perforated interval. Based on these conclusions a remedial job was designed and conducted successfully. Another HPT/SNL survey was conducted post workover. It confirmed the absence of any further flow behind casing and that all liquid production is happening from the targeted reservoir. Surface test data showed a rapid decrease in water production to 1% post workover. This paper highlights the importance of complementing the current practice of running conventional PL surveys with two additional services: the Spectral Noise Logging and Temperature simulation/modelling using a High Precision Temperature measurement.

ABSTRACT Successful identification, evaluation, and management of bottlenecks in a complex, offshore production processing system—though challenging—can significantly increase daily production for the system owner. Historically, such optimization plans were developed in relative isolation of the entire production system from wellhead to export pipeline. That approach benefits simplistic systems with sufficient ullage and in which discrete changes do not affect other flow system components. However, the Constitution platform in the Green Canyon area of the Gulf of Mexico, which was commissioned in 2006 with a nameplate capacity of 70,000 BOPD, is a complex system with four fields in varying stages of development. These fields have both dry and wet tree wells with varying fluid compositions and pressures flowing through the facility, which necessitates varying process requirements, making it challenging to manage. Such a system requires a holistic and focused approach by all technical and commercial disciplines. This paper focuses on a multidisciplinary process developed to identify, evaluate, and eliminate interdependent bottlenecks on the Constitution platform and its flowline network during a 16-month period. A multidisciplinary study was kicked off in 2017 to address these complex bottlenecking issues, and the resulting project achieved a 30% improvement in deliverability of the process system.

Abstract The paper describes the use of new generation of inflow chemical tracer application at Salym Petroleum Development Upper-Salym oilfield as a part of Smart Field project. This kind of well surveying using indicators that allow the evaluation of the inflow composition for each hydraulic fracturing port in horizontal wells remotely, without any additional risky and costly downhole activities. The new inflow chemical tracer technology is based on the use of nano-particle quantum dots, which give a level of high accuracy in quantitative analysis of fluid inflow. Markers, which are micromillimeter in size, are inserted into the polymer coating of the proppant. The technology involves the injection of marked polymer-coated proppant in the process of MHF (multi-stage hydraulic fracturing). Once the MHF is done, and the well is producing, the fluid samples are taken at surface and tested in a laboratory using machine learning software. Once the obtained data is interpreted, a flow profile of oil and water can be generated for each frac stage. One of the main advantages of marker technologies is that they provide data over a long period of time, with a significant reduction in operating cost. It opens the door for new opportunities in terms of more accurate reservoir characterization and better hydrocarbon recovery. The key element of the technology is the use of specialized intelligent machine-learning software based on Random Forest algorithm to produce production flow profile. The described methodology was used during the multi-stage hydraulic fracturing operation on oil wells 8105 and 8064 of Upper-Salym field. The volume of proppant injection at each stage was 20 tons, out of which 15 tons were of marked proppant containing a unique code for each stage. As soon as marked proppant has a contact with well fluid markers are emitted into fluid and sampling at the wellhead can be done any time when information required. The results of samples analysis are reports with graph showing quantitative distribution of water and oil production of each fracturing interval. The new generation of inflow markers allows for continuous production, surveillance and quantitative analysis of oil and water phase from each fracturing stage. This enables better decision making to optimize the production and make better decisions for water conformance interventions. This surveillance method does not require complex and risky well interventions or production shutdowns, making it substantially more cost effective than the existing conventional methods. Optimization of oil production, remote monitoring for risks minimization, reduction of operating costs - all these are the results of the introduction of Smart Fields technology systems in the Salym group of oilfields.

Abstract In a green field located in offshore Abu Dhabi, a new well was drilled in an oil-bearing zone and was completed with slotted liner inside a 6-in horizontal drain hole. Abnormally high gas rates were reported during the surface production testing of this well. This paper highlights the unique use of a new pulsed neutron tool combined with an advanced production logging tool for assessment of the well performance and identification of the source of gas breakthrough. This combination of advanced technology tools with measurements from array flowmeters, optical gas holdup sensors, and a new generation pulsed-neutron tool was deployed in the well to provide reliable flow type, borehole, and formation measurements in a gas environment. A multidisciplinary approach involving production engineering, petrophysics, and well integrity was essential in diagnosing this unexpected issue of high gas production. An integration of the various results from production logging, the pulsed neutron measurements, and open-hole and cement log data has helped in confirming the source of the produced gas. The acquired production log (PL) data revealed gas entry from the top of the lower completion and no presence of free gas below that depth. The zonal contributions from the horizontal lateral quantified from the acquired data also helped in assessing the productivity of the reservoir. The pulsed neutron log (PNL) measurements were acquired in the second run, which then helped confirm the borehole fluid properties and to identify and quantify the formation fluids. Combining the PNL and PL data helped identify the gas entry point accurately. Based on the integrated data interpretation, it was confirmed that the gas could not originate from the reservoir being produced through the lower completion and that there must be gas channeling downward through channels in the cement behind the casing from a gas reservoir above the oil reservoir. The unique use of the advanced PNL data and its integration with other log data facilitated the successful identification of the gas source and quantified zonal contributions in a challenging logging environment.

Abstract This paper presents a novel approach of continuously measuring drilling fluid rheology and density by use of sound signals. A unique apparatus is built with a series of pipe sections designed to exact pre-calculated dimensions to achieve equivalent standard shear rates as stipulated in the American Petroleum Institute (API) Recommended Practice 13D for measuring the rheology of oil-well drilling fluids (from 3 to 600 RPM). Acoustics waves are passed through the fluids of interest and their interaction is recorded and analyzed to deduce the density and rheological properties of the fluids. The concept of resonance as demonstrated by the Barton's pendulums are the basis of the methodology. Sound signals are known to exhibit a damping effect when passing through various media. Pairs of sensors are employed in this set-up and their signal response are first characterized and calibrated with fluids of known properties. Electric current is converted into acoustic signals by piezoelectric sensors mounted of the flowline which are then emitted through the fluids desired to be measured without interrupting the flow. A matching sensor receives these damped signed and reconverts them back to electromotive potentials for recording by a data acquisition unit. The signals are then analyzed by applying statistical techniques to interpret and obtain the fluids physical properties. Owing to the nature of the task, the goal of accurately achieving simultaneous measurement of density and viscosity is attained by applying an ensemble machine learning algorithm, known as Multivariate Random Forest. Pure chemicals and fluids of known properties form the training group on which the predictive model is built for subsequent testing on new mud samples flowing through each section. The pipe sections generate shear rates covering the standard range adopted in oilfield reports. Results from each pair of sensors are analyzed and compared with dial readings from rotational viscometers; these have shown to be within a narrow band of error. As a result of this work, the voltage outputs are sent continuously and in real-time to a processing computer that converts the values to dial readings at standard shear rates, while not disrupting the flow. This can aid in the better monitoring and surveillance of the entire fluid system of the well, which is highly beneficial to well control. The system can also be arranged to acquire gel strengths or how the fluid behaves after a fixed period of rest. Improvements can be made on the current procedures for fluid characterization which have remained relatively static for many years. This work engages the disciplines of rheology, acoustics and machine learning, creating a mechanism for continuous and real-time drilling fluid surveillance critical to the enhancement of safe development of petroleum resources.

Abstract This paper addresses the need and challenges associated with the clamp-on gas and oil flow and water-cut measurement techniques for efficient and reliable flow allocation and production management. This will be useful for production, as well as, reservoir engineering in both traditional and unconventional multiphase flow environments. Furthermore the paper reviews the advancements in the available clamp-on measurement techniques and evaluate their advantages and shortcomings in different flow conditions.

Abstract Since its discovery at 1971, numerous matrix stimulations were performed in South Pars field. However, there are still various challenges on stimulation job design and evaluation methods. In order to tackle these issues, fifteen matrix operations were selected to be analyzed from different phases of development project of the reservoir. The objective of this study is to introduce a new approach to figure out optimum acid volume (gal/ft), compare the effectiveness of diverters, calculate stimulation ratio (SR), and forecast post-acid production behavior from surface treating data. Modified inverse injectivity (I inv ) method, which is fully discussed by Safari et al. (2020) , is utilized in this study. Obtained data were analyzed in terms of I inv decreasing trend, I inv humps as well as pre/post-acid I inv during stimulation process. In addition, pre/post-stimulation surface testing data are gathered and analyzed. These data are coupled with post-acid I inv to find a correlation to predict production behavior of treated wells. SR is defined as the ratio of pre-acid I inv to post-acid I inv of a treated well. Finally, SR values are validated with available PLT data of two stimulation operations. Obtained results indicate that optimum gal/ft of acid depends on well conditions. In this regard, wells with high initial formation damage require more volumes of acid. In this regard, wells treated with 27/27 gal/ft design (27 gal/ft 28%HCl and 27 gal/ft 15%VES, i.e. Visco Elastic Surfactant,) were under-stimulated. Although, 53/53 gal/ft design seems to be adequate for low-skin wells, higher gal/ft would further enhance productivity of highly damaged wells. This result was confirmed by stimulation of a damaged well with 60/60 gal/ft design. Finally, the most reliable design applied in the field is 70/70 gal/ft so far. I inv analyses depict that better diversion is observed in wells with lower injectivity and higher damage. Generally, the magnitude of Iinv humps, which represents as a supporting evidence for diversion, decreases as stimulation proceeds. Furthermore, fiber–laden VES diverter exhibited better diversion than VES alone. Surface post acid drawdown at a specific production rate, e.g. 50 MMSCFD, is defined as the difference between shut-in and flowing wellhead pressures. Obtained results demonstrate that there is a direct relation between the post-acid Iinv and surface drawdown in this field. Therefore, production behavior of treated wells can be correlated by having access to post-acid Iinv. Ultimately, calculated SR values demonstrated average deviation of less than 10% with downhole PLT data. The novelty of this work pertains to utilization of the I inv method to evaluate performance of matrix stimulation operations. By applying this method, optimum volume of acid and diverter, diversion effectiveness, stimulation ratio as well as a prediction of post-acid surface drawdown can be obtained from surface treating data. The proposed methodology led to get better understanding of South Pars reservoir behavior during matrix stimulations. The same methodology can be applied to other carbonate reservoirs, too.

Abstract Liquid loading is one of the biggest challenges in operating gas condensate wells of a depletion reservoir. Analyzing this bottleneck using physics-based model estimations is one of the key methodologies in an integrated digital production system, which can help users to take preventive actions, thereby saving cost, time, and efforts considerably. This paper demonstrates the identification of the liquid loading condition in existing producing gas condensate wells using the analytical tools and automated workflows in an integrated framework. The analytical workflow to investigate liquid loading bottlenecking requires calibrated and representative well models as a first step. These representative well models incorporate a tuned compositional PVT model as a fluid parameter model, and such model outputs match with wells deliverability and historical production trends. Subsequently, the calibrated models are then integrated into a digital platform consisting of automated well analysis workflows. Along with various well performance parameters being analyzed, two key parameters for liquid loading debottlenecking, such as critical unloading velocity and the In-situ velocity, are investigated in the IAOM (Integrated Asset Operation Model) system for each well as the function of depth along well's completion. Furthermore, advanced dashboards present the analysis output in an instructive manner, driving user's engineering judgment to take preventive decisions. The Integration of framework with various corporate data sources provides a continuous stream of representative data that is utilized to estimate wells deliverability under the pre-defined operating envelope. As a result of the analysis, gas condensate wells that are suffering from liquid loading were identified using the integrated digital framework. Based on the production history and target monitoring, it was observed that these wells were unable to produce as their expected objectives. Identified wells were run through the production gas rate sensitivity analysis using the analytical tool, and as an outcome, the optimal production rate was calculated. Producing the well below this critical rate causes the In-situ velocity to drop below critical unloading velocity. Additionally, using the tuned and calibrated network model, the operating choke was identified to maintain the stable flow in the well and avoid further liquid loading. This choke size was provided to field operation for implementation and, thus, saved the cost and man-hour spent during the flowing gradient surveys. The case study demonstrates significant production improvements observed for these wells, thereby assisting the operator in reducing cost and time significantly. Using Integration of latest production optimization platforms not only provides tools to identify wells which are currently experiencing liquid loading problem but also healthy wells which might come across liquid loading problem in the course of production, thus helping in taking proactive remedial action. Furthermore, the integrated framework provides erosional velocity related data, which acts as a guideline while optimizing gas production.

Abstract Prior to field-scale development of chemical EOR processes, pilot tests are widely accepted in the oil industry as a standard method to determine the efficiency of the formulated chemicals. During such tests there can be significant differences in temperature between the injected and reservoir fluids. This results in a cool-down of the wellbore, near-wellbore and inter-well regions which can be aggravated in high temperature reservoirs. Key features of surfactant flooding, such as interfacial tension (IFT) reduction between the oil and water phases, depend strongly on temperature. As a result it is necessary to estimate the strength of this cool-down effect upon designing pilot tests. This is the topic of this paper which addresses several scales ranging from near-wellbore to pilot pattern. This work assesses the impact of temperature gradients during a pilot test on the efficiency of surfactant injection using advanced reservoir simulation. We first determine the temperature window seen by an injected surfactant solution with the aim of understanding how it may drive surfactant formulation. We then apply our findings on a pilot design study, with a model including a temperature dependent IFT. We analyse the sensitivity of given injection sequence and operational constraints to specific properties of the injected surfactant solution (low-IFT temperature windows) and then propose a methodology to determine the most efficient injection sequence for a specific surfactant formulation. We show that the temperature window encountered by the surfactant is very sensitive to thermal history of the reservoir and injection temperature. The analysis of chemicals slug thermal and compositional mixing with in-situ fluids is found to be a game changer for reliable pilot design and production forecasts. Obtaining the lowest IFT between oil and water phases is the key in surfactant flooding efficiency: as such the in-situ temperature profiles obtained by simulation and the formulation design at the laboratory should be closely linked. We demonstrate that the process is considerably sensitive to temperature and suggest as a result the following workflow for the design of injection sequences during a pilot test: 1) assessing the temperature window that will be seen by the surfactant using simulation, 2) designing an adequate surfactant formulation, 3) estimating an optimal and robust surfactant injection sequence using simulation, 4) iterating between the three previous steps until an optimal recovery is achieved with a laboratory-formulated, cost-effective surfactant. The impact of temperature on surfactant pilot tests is a specific, not so well documented subject, although it is a capital step in the feasibility assessment of a field scale deployment of surfactant EOR technology. Our workflow yields a reliable assessment of temperature landscapes seen by the injected fluids, which may then be used to test surfactant formulations from near-wellbore to interwell/reservoir scale (e.g. for designing and performing single well chemical tracer tests). As such it should be of interest to petroleum engineers, production engineers and chemists working on the design of chemical EOR processes.

Abstract An innovative and practical solution for well monitoring of pressure, temperature, inertial, and magnetic parameters is reported. Tiny and robust systems integrating microscale technologies for telemetry, wireless charging, and physical sensing were developed, characterized, and ultimately deployed on a live installation. The microsystems were designed and developed by the University of Michigan and characterized by Total S.E., whereas the intervention protocols were designed and implemented by TOTAL in TOTAL E&P CONGO offshore facilities. This work demonstrates how regular downhole monitoring of assets can be performed at low cost, thus optimizing production while also de-risking future development plans such as infield wells. This novel approach also reduces risks associated with conventional downhole monitoring methods.

Abstract A cased hole well with inflow control devices (ICDs) was logged for production profiling as part of a field trial campaign testing a new fiber-optic wireline system. Pulled by a conventional tractor, both the fiber-optic wireline and a set of conventional production logging tools (PLTs) were placed at the bottom of a horizontal wellbore, locating the fiber across the reservoir for sensing purposes. The well produced at two different choke settings, enabling both technologies to capture low flow rate as well as high flow rate. The main objective with the testing was to compare the two technologies for production flow allocation and learn more about fiber-optic analytics. The two different measurements were performed as close in time as possible. While the fiber-optic cable was sensing, the PLT was stationary and not logging, and while PLT was logging, the fiber optic was deactivated. From fiber optics, high-quality noise logging plots were generated with distributed acoustics (DAS), identifying the inflow points despite the relatively challenging acoustic environment. Propagating sound allowed for a profile of fluid sound speed to be established. Distributed temperature (DTS) was less useful on this job due to some accidental inflow of borehole fluid causing hydrogen darkening. This affected the multi-mode fiber more than the single-mode fiber; hence, DTS data could not be used. The wireline-based MAPS tool consisted of capacitance-, resistivity- and spinner-array. With the sensors located on bow springs, the tool detected various flow patterns 360 degrees around the borehole. The fiber-optic cable is located low side in a horizontal wellbore and might be affected by this in a laminated flow situation. Still, the fiber-optic sensing system managed to provide useful flow information, comparable to the PLT tool.