The increase in the count of fields with deteriorating flow properties and, as a result, long nonstationary flow, leads to an increasing spread of periodic lift method. Classic multiphase pipe flow models used by most commercial simulators are not able to account for transient processes occurring during intermittent operation. The purpose of this work is to develop a method for calculating the pressure distribution in the wellbore and pipelines, taking into account the unsteadiness of the multiphase flow, as well as its testing on the example of solving various problems of production management: analysis of bringing wells on to stable production, monitoring and optimization of periodic well performance, analysis of processes during the start-up and shutdown of processing trains of the oil gathering system.

The complex interbedded heterogeneous reservoirs of the Severo-Komsomolskoye field are developed by horizontal wells in which, as part of the pilot project's scope, autonomous inflow control devices (AICD) are installed to prevent early coning and gas breakthroughs in long horizontal sections and reduce sand production, which is a problem aggravated by an extremely low mechanical strength of the terrigenous deposits occurring in the Pokur formation of the Cenomanian stage in this area. The zones produced through AICDs are separated by swell packers. The issue of AICD effectiveness is discussed in the publications by Solovyev (2019) , Shestov (2015) , Byakov (2019) and some others. One of the methods used for monitoring horizontal sections with AICDs is production logging (PLT). However, due to the complexity of logging objectives, the use of conventional logging techniques makes the PLT unfeasible, considering the costs of preparing and carrying out the downhole operations. This paper provides some case studies of the Through-Barrier Diagnostics application, including passive spectral acoustics (spectral acoustic logging) and thermohydrodynamic modelling for the purpose of effective estimation of reservoir flows behind the liner with AICDs installed and well integrity diagnostics. As a result of the performed diagnostics, the well completion strategy was updated and optimised according to the log interpretation results, and one well intervention involving a cement squeeze with a straddle-packer assembly was carried out.

In order to improve tools for monitoring the reserves recovery and localization at the Gazprom Neft fields, as part of the technological strategy, a technology for geochemical control of reserves recovery has been developed. The use of geochemistry methods in identifying the targeted flow of fluids from a reservoir is based on the difference in fluids’ composition and properties from reservoir to reservoir. According to laboratory experiments, the accuracy of the geochemical predictions of miscibility based on a multiple linear regression model varies from 1 to 8% for oils and condensates, from 6% to 18% for gases, and from 15% to 34% for reservoir water (provided there is no pressure maintenance system in a reservoir). The technology was tested at Priobskoye field of Gazpromneft-Khantos LLC, which jointly operates Zones AS10 and AS12. The pilot program included 5 wells with pre-installed Y-tool assemblies. The advantage of this system is the ability to conduct tests in a well producing in a stable state with induced pressure drawdown. Simultaneous geophysical studies and wellhead sampling for geochemical studies allowed us to confirm matching of the results of dividing the inflow under the conditions of a well draining two or more target zones. The technology for geochemical control of reserves recovery will allow a breakthrough in the study of wellhead fluid samples in the near future, and such information will increase the success rate and information content of field geophysical studies by an order of magnitude. The advantage of the described technology is 100% coverage of the production well stock and the ability to predict miscibility for all types of fluids (oil, gas, and produced water).

Flow and injection profile monitoring in horizontal wells enhances the oil and gas field development efficiency, which is of particular importance when the target reservoirs have a complex geological structure, as is the case with oil-rim reservoirs located below a gas cap. The objective of this paper is to present the results of multi-well diagnostics carried out in order to estimate the flow and injection rates in Yarudey Field wells (Russia) and assess the downhole completion integrity status. When developing oil-rim reservoirs, flow and injection profiles need to be closely monitored so that gas and water breakthroughs along the length of thin beds and fractures could be promptly detected and appropriate remedial jobs planned. This task becomes more challenging in completions where multistage hydraulic fracturing was earlier performed, or the wells were cased with uncemented liners equipped with swell packers. To monitor the reservoir performance, advanced downhole diagnostics was performed in a group of wells in the field, where such reservoir-oriented techniques as passive acoustics and high-precision temperature logging were used. Application of the passive acoustic logging technique helped to identify reservoir flow zones and detect crossflows behind casing. The flow and injection rates were estimated through temperature simulations. Both these techniques were found to be useful, including those instances when the integrity of complex downhole completions was to be assessed. On the whole, the obtained results have proved the effectiveness of supplementing conventional production logging (PLT) with reservoir-oriented techniques.

Development of oil rims at oil-gas-condensate fields is accompanied by a high risk of gas coning which leads to well productivity losses followed by conversion of such wells to an idle stock. In order to increase the oil recovery factor of oil rims and to eliminate early gas breakthroughs, horizontal wells drilled in thin oil rims are equipped with autonomous inflow control system. The study describes the experience of AICD application for one of the largest fields in East Siberia with an oil rim and a large gas cap, where an integrated analysis of the AICD well performance was conducted for the first time in Russia. This analysis includes: choosing well-candidates, performing AICD lab testing, sector reservoir simulation, modeling of AICD effect, followed by the actual well performance analysis after running AICDs. All this became possible due to the well-organized cooperative work of the operator and the contractor. The wells included in this study were successfully put into production at lower GOR values compared to their surrounding wells

Modern technology of drilling and construction of horizontal wells allows for effective development of complex oil fields hard-to-recover oil reserves includes off low-permeability (less than 1-2 mD) and hyper-low-permeable (0.01-0.0001mD) fields. The latter in Russia include Bazhen, Domanic and Achimov fields. Their development provides for the mandatory completion of HW with Multiple-Fractured Horizontal Wells (MFHW). Experience in the development of layers of the specified type for Gazpromneft PJSC shows that the highest oil production rate is achieved if the MFHW system reveals not only the low-permeability rock matrix, but also captures the highly conductive (typically fractured) streaks — "strata-conveyors" (the latter may also be located in neighboring geological and stratigraphic differences). The difference in the permeability of such highly conductive layers and the hyper-low-permeable matrix of the host rocks can be very significant (up to 10 6 !). In addition to the positive aspects of the presence of highly conductive layers in the section associated with the achievement of high initial oil flow rates in new wells, in the process of further development, negative consequences may arise as a result of premature (even unpredictable) gas and water breakthroughs through narrow fractured layers. Is it possible to take into account the risks of loss of well productivity as a consequence of the pronounced geological heterogeneity of these fields, even if the scale of the impact of this heterogeneity is still difficult to assess by modern research methods? In this paper analyzes some of the results of core, logging, well testing and indicator studies with the allocation of characteristic features indicating the presence of local highly conductive fractured layers in the section of the oil the Bazhen-Abalak complex (BAC).

One of the most important tasks when developing oil fields with horizontal or directional wells is the inflow distribution monitoring along the wellbore. Possible irregularities in the inflow are primarily associated with heterogeneity in the filtration distribution and capacitive properties along the wellbore, unevenness in the depression distribution, possible overfilling of the wellbore, partial or complete blockage of sand filters by mechanical impurities or clay material, imperfect development of the wells (when part of the mud cake remains on the wall of the well), gradual clogging of the bottomhole zone pores, water breakthroughs and gas outs, or other reasons. Inflow profile monitoring allows identifying why the well performance has decreased and timely planning and carrying out appropriate geological and technical measures. Also, this information allows timely updating hydrodynamic models of field development to properly make strategic decisions. This paper presents the results of bench tests of a new active thermometry technology using a distributed temperature measurement system

The well integrity monitoring including Sustained Annulus Pressure (SAP) assessment on offshore stationary platforms in the conditions of a limited number of well slots plays an important role in the development of oilfield with thin oil rims and a massive gas cap. The presence of SAP leads to uncontrolled release of gas or liquid to the surface, disruption the operating condition of the wells and its completion components, that overall can result to severe accidents at the offshore oil and gas production facility. Another difficulty that SAP brings is secondary gas cap accumulation across untargeted reservoir zones that might lead to blowouts in operating wells. To identify the causes of SAP, constant monitoring of annulus pressure, as well as proper diagnostics are needed. One of the most reliable and effective methods for identifying SAP causes is Through-Barrier Diagnostics that able to accurately localize reservoir-sources of SAP behind multiple casing strings in the wells, which helps production engineers further production strategy and weighted workover planning. Conventional diagnostics on identifying SAP sources is significantly limited by complexity of the well construction and downhole equipment. This paper describes using of Through-Barrier Diagnostics on the sources of SAP identification on the ice-resistant stationary platform named after Yuri Korchagin, detailly explains the approach and challenges on real case studies. High precision temperature and passive spectral acoustics play a key role in described technique. Passive spectral acoustics, which have a scanning radius of about a few meters, helps to detect fluid flows in the reservoir and behind casing channels in cracked cement.

For the first time, one of the Russian oil company empowered to change standard approach to well production optimization by using a new generation of intelligent completion technology - the all-electrical system with fine inflow control and downhole flow characteristics measurements that were previously unavailable in real time. The experience of optimization approach, which is unique for both the Russian and the world oil industry, is described in this article. The standard approach to well optimization was time consuming and, in some cases, associated with comprehensive testing and well interventions. The new approach allows testing and optimization of wells in real-time within shortest period with no production logging, well shutoffs and production loss, and allows to obtain phase rates and fractional composition of the flow for each well interval. The described technique was consistently introduced and improved by x-segment specialists from production and science departments. Accumulated real time data and special downhole testing made it possible to obtain a unique knowledge about zonal flow behavior during various stages of well operations stable work, well testing, build ups, shut offs, well starts, clean ups and optimizations. The new technique at this stage allows: Optimize well clean-up; Introduce new well testing procedure with minimum production, Minimize interventions; Reduce time for full well optimization cycle to 2 days; Introduce procedure for well shut-in preparation for wells with high GOR and watercuts; Minimize cost and risks associated with interventions, zonal testing, optimizations. Background for the described technique introduction are innovative scientific research and experiments with the aim of obtaining fractional composition and phase rates in real time with a minimum set of downhole sensors. The article describes the theoretical foundations of the approach, innovative areas of research and methodology for improving the models and applied correlations. Scientific solutions coupled with implementation of advanced completion technologies, machine learning methods, as well as depth of field experience have improved the approach to solving well optimization challenges of wells on the North Caspian field. The experience gained from the first three wells was used to expand the technological and interpretation capabilities of the described solutions. The one of the key advantages of proposed optimization methodology applied on wells with presented technological equipment is simplicity and elegancy of approach. The total number of downhole valve position change during various operations for three wells exceeded 1500 within less than 1 year of operation time. To the moment, the methodology, the experience gained, the results of the approach implementation are unique for the oil industry. The presented technologies and digital solutions make it possible to improve well management strategy significantly and, of course, will be interesting to engineers of field management department.

Constant growth of commercial hydrocarbon (HC) consumption requires for the oil and gas industry to be involved into exploitation of unusual oil and gas reserves, preventing HC supply shortage on the global market. The fields with conventional reservoirs being actively developed during the last century have a tendency now to reduction of routine parameters of HC production. Now more and more attention is being attracted to tight reserves, which have to be studied in unconventional ways. This article focuses precisely on complex reservoirs, in which reserves are classified as tight. A complex quantitative assessment using several different technologies for long-term monitoring under difficult conditions has shown favorable results.

Acid treatment is a common well stimulation technique widely used for both oil and gas wells. However, there is a challenge, that for any given acid solution, rock lithology and permeability, and reservoir conditions, there are optimum values of acid injection volume and rate. Deviation from these optimal values during stimulation treatments reduces the acid job efficiency. We developed a robust and efficient method of identification of the optimum parameters based on digital core approach. The developed workflow includes: a) construction of a digital avatar of a core sample using 3D microCT tomography; b) pore-scale direct reactive flow modeling using a combination of the chemical kinetics/thermodynamics (in assumption of partial local equilibrium) with the method of density functional theory in hydrodynamics (an efficient tool for pore-scale modeling of multiphase flow able to handle different complex physical phenomena); c) core scale simulations in the framework of the Darcy based approach using upscaling from the results of the direct pore-scale simulations; d) input of the obtained parameters into the acidizing simulator to determine optimum acid type, rates, and volumes. We illustrate the developed workflow on example of an optimum injection rate determination in the case of Silurian dolomite dissolution by hydrochloric acid. The pore-scale simulations were performed using 3D microCT models with 2.5 μm/voxel resolution. These simulations allowed to determine the dependence of dolomite dissolution rate on the fluid injection rate and predict the transport properties of damaged rock. The correlations obtained from high resolution simulations were then applied in core-scale modeling of dissolution process using continuous Darcy based model (with 100 μm/voxel resolution). The transport properties of a core were populated using the results of pore scale simulations. Then several core scale simulations of dolomite dissolution with different acid injection rates were performed to obtain numerically the dependence of its influence on the number of pore volumes injected until the breakthrough (PVBT). PVBT dependence on the injection rate in a form of characteristic curve was incorporated into the advanced acidizing simulator. Being calibrated this way, the simulator was then used to model acidizing treatment in a dolomite reservoir with the similar properties as digitally acidized core. Modeling showed that post stimulation skin values are lower and expected wormhole length is bigger when digitally calibrated pore volume to breakthrough (PVBT) curve is used, if compared with modelling of the same treatment with non calibrated acid-rock interaction curves. Consequently, outcomes of this well scale modeling suggest that the use of digitally calibrated PVBT curves results, for this case, in optimization of required acid volume and associated operational footprint. The suggested approach improves the process of obtaining PVBT characteristic curve by application of digital core analysis technique. It allows to test numerous "what if’ scenarios and to evaluate the effect of different factors on mineral dissolution rate at pore scale. This paves the way for improvements in acidizing job design by increasing the consistency between the models used for reactive flow modelling and pore scale heterogeneity of real rocks.

An efficient hydrocarbon field development requires implementing the current field production control accompanied by various surveys. Historically, classic approaches do not yield favourable results and ensure high information value,which results in the necessity for state-of-the-art technologies. One of these technologies could be the production logging using markers. The goal of this article is to study various sampling techniques for convergence of quantum markers identification results during the horizontal well injection logging. The present article is dedicated to the studies comprising of a comprehensive reservoir fluid sample analysis with subsequent production logging evaluation of a multi-stage horizontal well at Sredne-Nazymskoye oilfield. The article covers the oil and water inflow monitoring in a horizontal well treated with 15-stage fracturing. The technology, which serves a basis for this analysis, involves using a marked proppant with polymer coating. Flow profiles are evaluated by calculating the markers of different codes in a fluid sample, and every signature (code) corresponds to a particular interval where a man-made crack is induced. For this study the special sampling schedule was made involving an extensive reservoir fluid sampling in order to perform representative selection and making references to external and engineering factors such as well operation conditions, flow pattern, flow rate, volume components, etc. Test review allowed getting a general idea of how reservoir fluid will be sampled at non-conventional deposits qualified as the hard-to-recover reserves in order to improve production logging information value both at qualitative and quantitative levels.

The paper describes the experience of lift models creating in case of oil rims of the Tazovskoe and Novoportovskoye fields. There is analysis of the actual well performance with high gas oil ratio, the software capacity to the gas-liquid flow modeling in the well, and review of existing analytical techniques for unknown model parameters prediction. The problems and limitations of existing methods are emphasized and approaches to their solution are proposed.

In this paper, we demonstrate the ability to run an adaptation on field data for a steady-state multiphase pipe flow model for calculating the bottomhole pressure of an inclined well using the deviation survey data, wellhead parameters (pressure, phases flowrates and properties), and the temperature distribution along the wellbore. In the underlying model published earlier in different modifications ( Baryshnikov et al., 2020 ; Kanin et al., 2019 ), we divide the well into segments and perform the hydraulic calculation of the pressure distribution along the wellbore via the marching algorithm in which the set of PVT correlations and the segment model are utilized. The distinguishing feature of the utilized approach is a data-driven segment model required for calculating the pressure drop along the chosen part of the pipe. This model is based on Artificial Neural Networks (ANNs), which firstly trained on the synthetic data and lab measurements, and after that, additionally tuned on the real field data collected on two wells during the flowback period conducted via the free-flow production method. During the optimization of the ANNs on the field data, we imply the quasi-steady-state approximation of the multiphase flow, i.e. the transient flow is considered as a sequence of the stationary states. In work, we also carry out the comparison of the prediction capability of the constructed pipe segment model with several most common multiphase flow correlations and mechanistic models (within the frame of the marching algorithm) and demonstrate its more accurate outcome. As a result, we develop a method for calculating the flowing bottomhole pressure value adaptable on the required field data. The model adapted on field data allows estimating the flowing bottomhole pressure at each time moment (assuming the quasi-steady-state flow) which is particularly important in the absence of the bottomhole pressure gage at the well.

In order to efficiently asses pressure support during the field development that bears a complex structure of the void space, it is extremely important to understand how existing wells affect each other, this issue was solved at one of the fields in Tatarstan through unique cross-well surveys. The conventional way to solve the problem of assessing reservoir connectivity consists of analysing seismic surveys, analysing the tectonics and sedimentology at focus region, conducting tracer surveys, interference tests, and production analysis. However, all of aforementioned methods display substantial deficiencies, for instance: poor seismic sensitivity towards low-amplitude faults, poor degree of detail of tectonic analysis, poor tracers representatives in complex vertical and lateral reservoir heterogeneity, if most permeable thin layer lateral anisotropy differs greatly with the main layer anisotropy, huge production losses during interference test along with receiver well shut-ins, and ambiguity in the estimation of interference with the production analysis. That's why is was decided to use pressure Pulse Code Testing ( PCT ) ( Kamal, M. M. 1983 ; Ahn, S. et al. 2010 ; Aslanyan, A. et al. 2015 ; Aslanyan, A. et al. 2016 ) that managed to overcome those problems and avoid production deferment. The values of reservoir diffusivity and transmissibility are calculated from the recorded in revisers moment of arrival and the amplitude of the pressure disturbance from rate changes in generators. Based on the registered pressure pulse amplitudes we can estimate the influence of generator monthly injection on the pressure at receivers ( Myake-shev, N. 2017 ). The obtained injector influence on producing well is extremely low, and indicates a poor efficiency of pressure maintains system at the tested area. That implicitly indicates on unproductive injection ( Zheng, S. 2010 ). In addition to a subsequent production logging it was confirmed that there is in fact a presence of a significant amount of unproductive injection due to cross flow downstairs. That was reducing the efficiency of the pressure support in the study area. This placed the start to a set of extended surveys aimed at selecting of the most appropriate injection targets of the injection wells to improve the efficiency of the pressure maintains system as well as oil production increase.

We propose a novel technique to calculate bottomhole pressure (BHP) during well clean up and production using machine learning (ML) approaches solely based on the datasets commonly collected at surface from multiphase flow rates, wellhead pressure, wellhead temperature and fluid properties. We show that the proposed technique enables creating a digital analog of the downhole pressure gauge to provide stable and safer measurements of downhole parameters. The proposed solution was built by use of classical supervised ML methods such as linear regression, regressions with regularization, and decision trees. These models were trained for given well completion and trajectory using the field datasets consisting of a time series of various surface physical data (such as rates, wellhead pressure, and temperature), acting as input features and target value data measured by downhole pressure gauge. Once the training is complete, these algorithms can predict BHP variations using only surface data. We demonstrate that the ML models are capable of predicting BHP using wellbore-specific physical parameters and showing decent prediction quality with error less than 5% during transient flow regime. Moreover, we show that these ML models are capable of evaluating the bottomhole pressure almost instantaneously, unlike traditional numerical simulations that may require certain time for calculations. The proposed approach can be an affordable and accurate alternative to traditional solutions including either inverse task problem of BHP calculation or physical measurements with pressure gauges. In the classical approach, the transient multiphase flows are studied using mathematical models and numerical simulators. In this work, ML models applied to solve the BHP prediction problem demonstrated a low prediction error and a fast prediction time. The results can be used to efficiently control the drawdown during well clean-up and production.

The active building of HW with MSHF use for ensuring their effective development in low-permeability reservoirs, but there are certain difficulties with getting completely information for making the right decisions during control of development. As part of the work performed, the main uncertainties and the further application of research results for estimates the profile of horizontal well (HW) with multi-stage hydraulic fracturing (MSHF) for planning the necessary geological and technical actions based on more than 20 operations at the South Priobskoye field are shown. The following field geophysical tests were executed in wells: PLT with Y-tool and CT + spectral noise logging module; PLT during compression with CT + multi-sensor flow meter; PLT with a well tractor; tracer studies (proppant, frac sleeves); thermometry with using fiber-optic system in injection and production wells.

The purpose of the report is to share with experts some of the accumulated experience in the planning and interpretation of thermohydrodynamic data of multilayer injection and production wells in combination with noise measurement. The description of the mathematical model of thermohydrodynamic processes in the system "wellbore – jointly operated reservoires", which takes into account convective heat transfer, thermal conductivity and barothermal effect in the reservoir, is given. The temperature model of the well takes into account the convective heat transfer, heat transfer with the environment. Annular flows and modify properties of wellbore zone are simulated. The article describes the geological properties, the technology of production well logging, mathematical models of thermohydrodynamic processes, algorithms of proccesses and quantitative data interpretation that tested in practice. Geological and technological measures to increase oil production are recommended based on the analysis of the results. The quantitative interpretation of thermohydrodynamic data based on the use of the simulator is demonstrated by the example of one injection well of SPD. There are results of production logging on several modes of injection and transient pressure and temperature. Production well logging (PL) was performed by several combined tools, such as different types of flowmeters, noise meter, temperature, pressure and composition sensors. The first research was carried out by a standard production logging unit, in the second case, an additional noise tool with fixed frequency windows was used, in the third one a broadband acoustic noise toll was used. The results of the interpretation of the standard production well logging, additional information on the noise data are analyzed. The temperature and pressure fields in the wellbore and in the reservoir are numerically simulated. As a result of the inverse problem solution, the contribution of each layer to total injection was determined, including the contribution of the overlapped tubing interval. The following results were obtained: The injectivity profile of the well at two different injection modes. Behind-the-casing flows of fluid above and below the perforated zone. A quantitative assessment of behind the casing flow contribution in two different injection modes is made. The location of casing leakage above the perforated zone is revealed, as well as a quantitative assessment of the contribution of fluid inflow from this location in two different modes of injection is made. The internal fluid circulation between the casing leakage point and the perforation zone is determined. As a result of simulating it was established: Behind-the-casing flow down is insignificant and repair and insulation works are not required. Behind-the-casing flow upwards is insignificant, but its effect is associated with long-term injection into an undeveloped formation. When the injection pressure decreases, this formation begins to push the perforated reservoir. Repair and insulation works are required. Thus, the combination of a standard production logging unit, acoustic noise measurement and simulation of thermohydrodynamic processes allowed to eliminate uncertainties in the interpretation of data and to give clear recommendations for repair and insulation works.

Tracer (marker)-based horizontal well studies are becoming increasingly common in the oil industry with the application of the innovative inflow indicators allowing production logging in horizontal wells along the well. This allows users to obtain analytical information for the effective management of production and field development processes. These technologies can significantly reduce costs and risks for oil and gas producing companies compared to conventional logging methods. The objective of the present study was to evaluate the production logging of horizontal wells stimulated with multi-stage acid fracturing. The monitoring technology was based on injecting marker dispersions into formation together with the acid stream during hydraulic fracturing. Acid-resistant monodisperse polymer microglobules, encoded for each of the stages using quantum dots and selectively interacting with water and oil, were used as marker inflow indicators. Acidic multi-stage fracturing was carried by utilizing a unique technology from "toe" to "heel" using a piercing perforator and CT with the injection of acid through the annular space. The separation of acid fracturing zones was carried out by the axial array packer. After the completion of stimulation works and after putting the well into operation, formation fluid sampling from the wellhead was carried out and analyzed to determine the number of tracers of each code. Based on the obtained analytical data, the formation fluid inflow profile along the horizontal well was built, allowing us to analyze the stimulation efficiency for each of the acid fracturing stages. Additionally, tasks such as the selection of the type and formulation of marker dispersions, their testing for compatibility with hydrochloric acid and hydraulic fracturing gel, working out the method for supplying tracers to the well and their placement in the formation, and evaluating the tracer particles adsorption degree in the rock were solved. Unlike conventional production logging in horizontal wells, the applied technology does not require special means of tool delivery and minimizes the risk of downhole tools getting stuck in the well and ambiguous data interpretation. It also does not require significant working costs. During the course of the work, the acid resistance and the physicochemical stability of the selected flow indicators in reservoir thermobaric conditions were confirmed. For the first time, production logging was conducted using the carbonate formation type and multi-stage acid fracturing, during which the inflow indicators were placed in eloxated acid fractures with long-term selective interaction of tracer particles with formation fluid. Based on the work results, geological and technical information was obtained for further planning of efficient geological and technical measures and additional oil recovery.

Expanding the share of unconventional oil and gas reserves involvement shifts the focus to analyzing well productivity increases. The cost of horizontal wells stimulation for increasing oil recovery rate carried out using multi-stage hydraulic fracturing is much higher. This requires the involvement of new technologies and services to facilitate optimal drilling, completion and stimulation returns. The use of developed technology to determine inflow profiles allows oil and gas producing companies to efficiently determine well productive intervals, thereby indicating high production rates and maintaining the profitability of facilities put into operation by eliminating non-productive intervals. These data allow planning field development with higher profitability due to increasing the oil recovery rate.