Production Logging Tool Research Articles

Unraveling the hidden relationships between seismic multiattributes, well-dynamic data, and Brazilian pre-salt carbonate reservoirs productivity: A shallow versus deep machine-learning approach

During the initial phases of an E&P project, the most reliable data on the reservoir’s deliverability are acquired via drill stem tests (DST), which provide the productivity per flow unit whenever production logging tool data are available. However, DSTs are restricted to a few kilometers, whereas seismic data cover large areas. The integration of these data has been challenging, particularly due to the difference in scale between them. So, a new workflow to determine the relationship between poststack seismic attributes and reservoir productivity using classic supervised (shallow) and deep-learning regression algorithms was developed. The DST parameters were predicted over the entire seismic cube, which can be extremely valuable for the decision-making process. The data set is from the Brazilian deep-water presalt carbonate reservoirs of the Mero Field, which is a well-explored area with a plethora of test and production data. It is adjacent to an underexplored Central Libra appraisal plan area, which is covered by the same seismic survey. Thus, any relationships between seismic attributes and well productivity data observed at the Mero Field are extrapolated to the adjacent underexplored area. Ten seismic attributes and DST data from 10 wells of the Mero Field were used to train shallow and deep-learning supervised regression algorithms for the prediction of flow capacity and productivity index seismic cubes. Twenty development wells (blind tests) were used for the assessment of our predictive models. The highest percentage of correct predictions at the blind test wells (85%) was obtained with random forest regression using six attributes derived from a spectrally balanced full-stack volume, and neither amplitude-variation-with-offset nor inversion data were needed. Deep learning provided lower performance (75%) at a higher computational cost. It demonstrated a new reservoir derisking tool that can be used for project optimization in areas covered by the same seismic survey.

The impact of fractures and planar structures on the quality of the Upper Jurassic Mozduran reservoir, Kopet Dagh basin (Northeast Iran)

In this study, based on stereographic projections, two sets of planar structures were identified in the Mozduran reservoir, a prolific reservoir in Northeast Iran. The first set includes shallow structures, consisting of stylolites, solution seams, dense veins, and bedding planes. These structures were created by both sedimentary and diagenetic processes and do not have much effect on reservoir quality. The second set includes structures are related to deformation, and these have a substantial impact on increasing the reservoir quality. To investigate the relationships between the types of fractures and their respective influences on reservoir quality, the production logging tool (PLT) gas production rate data was utilized. This analysis revealed that in fractured zones 2 and 4 of Mozduran reservoir, where fractures and flat structures have increased the quality of the reservoir, the PLT gas production rate also increases. Conversely, in areas where filled fractures and diagenetic processes have negatively affected reservoir quality, the PLT gas production rate decreases. This pattern indicates the contrasting impact of planar features on reservoir quality. Moreover, a higher frequency of fractures corresponds to a higher permeability in the Mozduran reservoir of Well #B, whereas a lower frequency of fractures corresponds to lower permeability in that reservoir in Well #A. These relationships confirm the positive influence of fractures on the Mozduran reservoir quality. The study results reveal that deformation variables in the examined reservoir have greater impacts on its quality than the sedimentary and diagenetic porosity/permeability components, but those impacts can have both positive and negative consequences.

Prediction of Production-Inflow Profile of a Well Producing Single-Phase Flow of Slightly Compressible Fluid from Multilayer Systems by Temperature and/or Pressure Transient Data

Summary This study focuses on the prediction of the production-inflow profile of a well producing a single-phase flow of slightly compressible fluid (water or oil flow) in a multilayered system using the layer permeability and skin values estimated by history matching spatial and temporal temperature and/or pressure data sets along the completion interval. Such data may be acquired by wireline formation testing, production-logging-tool (PLT), or distributed temperature sensing (DTS) fiber-optic cables. We use an in-house thermal, transient coupled reservoir/wellbore simulator developed during this study. It solves transient mass, momentum, and energy conservation equations simultaneously for both reservoir and wellbore. The effects of the Joule-Thomson (J-T), adiabatic expansion, conduction, and convection are all included for predicting the flow profiles across the wellbore. The results from our in-house simulator are verified with the results from a commercial simulator for the single-phase fluid flow of a vertical well producing geothermal brine and oil in a two-zone multilayer system. We also compare the results from our rigorous transient coupled wellbore/reservoir model with the results from a model assuming steady-state thermal wellbore model used in the previous studies. We find that the steady-state thermal wellbore model used in the previous studies that ignore accumulation terms in mass, momentum, and thermal energy balances is a reasonably accurate model for predicting wellbore pressures and temperatures when it is coupled with a nonisothermal reservoir model for slightly compressible fluid because the transient effect in the wellbore is less important with the slightly compressible fluid. We investigate the nonlinear parameter estimation problem based on the use of single or multiple observed temperature and/or pressure (if available) profiles recorded spatially inside the wellbore and at the sandface. The purpose is to identify if the wellbore or sandface data profiles are more useful to accurately estimate the permeability and skin information and predict a production-inflow profile of the well depending on the representation of an actual multilayer system by a reduced-layered or fine-layered model. We show that using an upscaled-layered model (e.g., representing each heterogeneous layer with a lumped single layer with uniform permeability and skin) provides estimates that are more toward the thickness-average permeability and skin factors of the layers and may not provide a good prediction of the well’s production-inflow profile. We show that including the sandface temperature data in regression worsens, while the use of wellbore temperature data sets improves the quality of parameter estimation if an upscaled multilayered model is used. We also show that regressing on multiple temperature profiles, preferably at the sandface, alone could be used to predict the production-inflow profile accurately if a “fine” multilayered heterogeneous model is used. We also investigate if including or excluding the temperature and/or pressure measurements at the nonperforated sections along the completion interval could help enhance the parameter estimation problem. The results show that when multiple profiles of temperatures including the data at nonperforated zones at different production rates are regressed, reliable estimates of the individual layer properties that predict the production-inflow profile accurately can be obtained, though layer permeability and skin factors may often exhibit wide 95% confidence intervals and high correlations among them. Adding sandface or wellbore pressure data, if available, into observed data sets in history matching always improves the quality of parameter estimation.

Slickline-Deployed Fiber-Optic Cable Provides First Production Profile for High-Temperature Gas Well

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215512, “Slickline-Deployed Fiber-Optic Cable Provides First-Ever Production Profile for High-Temperature Gas Well,“ by Stuart Berry, SPE, Expro, and Danu Dirya, SPE, and Graeme Cowie, SPE, TotalEnergies, et al. The paper has not been peer reviewed. _ Distributed fiber-optic sensing (DFOS) allowed the continuous gathering of flow-profile information from a high-temperature, high-rate gas well. The objective of the case study described in the complete paper is to demonstrate that thermal inversion modeling can be used to produce a production-flow profile in an environment where conventional production logging is not possible. As a result of deploying DFOS, data can be acquired at more-realistic rates. Through performing of thermal inversion of distributed temperature sensing (DTS) data and analysis of distributed acoustic sensing (DAS) data, a more-accurate flow profile was achieved. Introduction Culzean is a high-pressure/high-temperature gas condensate field in the central North Sea. The main productive interval for the field is the Triassic Joanne sandstone deposited in a semiarid continental fluvial environment. The Jurassic Pentland sandstone deposited by meandering fluvial systems also contains significant resources. Initial reservoir pressure was 936 bar; the temperature was 170°C. The development consists of six production wells, five from the Joanne and one from the Pentland. While the reservoir interval is relatively thick, the depositional environment created a very layered reservoir with significant variability in reservoir quality. Flow-profile data over the reservoir has traditionally been acquired using production-logging tools with spinner velocity and pressure and temperature measurements. Production-log deployment can be problematic in high-rate wells, particularly when tubing is restricted because of pipe deformation or deposits in the tubing. In the Culzean field, several wells were selected for flow-profile monitoring. Previous slickline operations indicated that conventional production logging would be ineffective. Modeling showed significant tool-lift risk, meaning that the well could only be flowed at approximately 25% of its normal operating rate. A previous attempted production-logging campaign in the well resulted in no valid data acquisition but incurred a direct cost of $700,000 and a deferral of 10 days production estimated at a cost of $10.8 million. An alternative acquisition method was investigated to obtain production-profile data while minimizing risks associated with conventional production-log deployment. DFOS provides a continuous measurement over the entire length of the well for temperature and acoustic noise. A high-temperature slickline DFOS wire could allow Culzean well data acquisition under flowing conditions. Technology Selection Data acquisition was divided into a shut-in phase and a flowing phase. For the shut-in phase, a simplified production-logging toolstring was used to measure any crossflow over the reservoir section. The flowing phase would consist only of DAS data over the reservoir section, with a simple pressure/temperature memory tool in the sump of the well. The DFOS data would gather shut-in data before opening the well up to flow. For the conventional tool shut-in string, an inline caged spinner was selected.

Integration of electromagnetic, resistivity-based and production logging data for validating lithofacies and permeability predictive models with tree ensemble algorithms in heterogeneous carbonate reservoirs

This study develops an innovative workflow to identify discrete lithofacies distributions with respect to the well-log records exploiting two tree-based ensemble learning algorithms: extreme gradient boosting (XGBoost) and adaptive boosting (AdaBoost). In the next step, the predicted discrete lithofacies distribution is further assessed with well-log data using an XGBoost regression to predict reservoir permeability. The input well-logging records are gamma ray, neutron porosity, bulk density, compressional slowness, and deep and shallow resistivity. These data originate from a carbonate reservoir in the Mishrif Basin of southern Iraq's oilfield. To achieve a solid prediction of lithofacies permeability, random subsampling cross-validation was applied to the original dataset to formulate two subsets: training for model tuning and testing for the prediction of subsets that are not observed during the model training. The values for the total correct percentage (TCP) of lithofacies predictions for the entire dataset and testing subset were 98 and 93% using the XGBoost algorithm, and 97 and 89% using the AdaBoost classifier, respectively. The XGBoost predictive models led in attaining the least uncertain lithofacies and permeability records for the cored data. For further validation, the predicted lithofacies and reservoir permeability were then compared with porosity–permeability values derived from the nuclear magnetic resonance (NMR) log, the secondary porosity of the full-bore micro imager (FMI) and the production contribution from the production–logging tool (PLT). Therefore, it is believed that the XGBoost model is capable of making accurate predictions of lithofacies and permeability for the same well's non-cored intervals and other non-cored wells in the investigated reservoir.

Excessive Water Production Analysis in the Abu-Attifel Oil Field Using Chan's Diagnostic Plots

Excessive water production is one of the major problems in mature Libyan oil fields. Water production has the potential to reduce the productive life of oil and gas wells while also causing serious issues such as tubular corrosion, fines migration, and hydrostatic loading. The aim of this paper is to diagnose and evaluate excessive water production mechanisms in the Abu-Attifel Oil Field using Chan’s diagnostic plots. This technique was applied to seven wells in the Abu-Attifel oil field. After a strong depletion phase, water injection was set up and started in the field in 1974. The Chan’s diagnostic plots method is applied using Microsoft Excel format to calculate and plot the derivative response to understand the excessive water production mechanism. The diagnostic plots showed some random and noisy trends on both the WOR and WOR’ plots; hence, they provide a controversial basis for characterizing water production based on surface observation of production trends. The multilayer channeling with production changes could be one reason for the excessive water production in the studied wells. The results obtained need to be verified by close monitoring using production logging tools (PLT) and well testing techniques to ensure breakthrough time and identify the main reasons for excessive water production

Application and Analysis of Array Production Logging Technology for Multiphase Flow in Horizontal Wells

Production logging (PL) instruments play a pivotal role in the comprehensive management and monitoring of oil and gas reservoirs. These devices facilitate the resolution of complex flow diagnosis challenges throughout the life cycle of hydrocarbon field exploitation. However, the advent of highly deviated well drilling technology has exposed certain limitations inherent in conventional centralized logging sensing techniques. When fluid flow within horizontal wells becomes segregated or even laminar, these traditional methods struggle to accurately decipher the zonal productions of oil, gas, and water. To address this challenge, multi-array production logging tools were developed in the late 1990s. Historically, these tools were characterized by considerable lengths, reaching up to 30 feet for an entire suite incorporating flow speed and holdup sensors that were not always collocated. Despite the integration of multiple sensors, uncertainties in determining flow profiles persisted. In this paper, we propose a novel integrated multi-parameter evaluation method based on measurements from a recently developed ultracompact flow array sensing tool, aimed at enhancing the accuracy of reservoir evaluation. The validity of the multi-parameter method is substantiated through a comparison of the new tool with an industry benchmark array PL tool on the same well. By combining the monitoring results, an optimization strategy for oil and gas extraction is presented, which is expected to improve the oil and gas recovery rate, thereby providing guidance for subsequent extraction endeavors. Moreover, we demonstrate how this innovative integrated workflow significantly enhances energy savings and efficiency, further underlining its value in modern oil and gas field management.

Vaca Muerta: Improved Fracture Width Distribution and Classification of Natural Fracture Widths Based on Outcrops, Cores, and Microresistivity Images Data

Summary Natural fractures in Vaca Muerta are very complex, such that their fracture width distributions cannot be analyzed simply by considering normal, log-normal, or log-log distributions. Natural fractures are commonly classified as macrofractures or microfractures; however, no consistent fracture width is attached to those fractures. In this study, two new approaches are proposed; an improved fracture width distribution and a classification for natural fractures that encompasses all physical widths found in petroleum reservoirs. The method developed in this study first evaluates the distribution of natural fracture widths from outcrops, cores, and microresistivity images of Vaca Muerta shale. An improved fracture width distribution is established through a variable shape distribution (VSD). The model provides a good fit, even if the shape of the distribution deviates from generally accepted distributions. This improves the accuracy of fracture width and intensity prediction, which is useful in generating synthetic production logging tools (PLTs) to estimate productivity from fractured intervals. Subsequently, a consistent classification for natural fractures is introduced to cover all fracture widths found in petroleum reservoirs. Results indicate that fracture widths in Vaca Muerta shale range between 0.0003 mm and 7 mm for outcrops, 0.0003 mm and 2 mm for cores, and 0.01 mm and 2 mm for microresistivity images. The VSD model provides a good fit of fracture widths from the three sources, without truncating any of the data. Truncation of data is usually required when using generally accepted distributions. With this improved distribution, size pattern extrapolation can be performed with greater accuracy. The physical widths can also be translated into hydraulic apertures to generate theoretical PLT. This is useful for estimating relative petroleum production potential from each fractured interval and for identifying future refracturing zones. Additionally, the study gives origin to a consistent classification of fracture widths that has application in Vaca Muerta and other oil and gas reservoirs. Five subclasses are introduced, which are megafractures (> 10 mm), macrofractures (1–10 mm), mesofractures (0.1–1 mm), microfractures (0.01–0.1 mm), and nanofractures (<0.01 mm). A careful review of the literature indicates that there is ambivalence as it is hard to find a clear and precise terminology that encompasses the entire range of fracture widths. The proposed classification eliminates that difficulty. In this paper, for the first time, a consistent fracture width classification is developed that encompasses the whole spectrum of widths found in petroleum reservoirs. It has wide application in Vaca Muerta, where widths, derived from outcrops, cores, and microresistivity image data are matched with a VSD model. Furthermore, the proposed classification can be used in other oil and gas reservoirs, thus eliminating the fracture width ambivalence found many times in the geoscience and petroleum engineering literature.

Subsea Multilateral Oil Producer Evaluated With Acoustic and Production-Logging Tools

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 210299, “A Subsea Multilateral Oil Producer, Completed With AICD Sand Screens and Selective Inflow Valves, Is Evaluated by Combined Acoustic and Production-Logging Tools, Identifying the Sand-Producing Branch and a Tubing Leak in a Single Operation,” by Duncan Troup, SPE, Archer; Tim Griffin, SPE, Three60Energy; and Minh Pham, Aker BP, et al. The paper has not been peer reviewed. _ A horizontally completed subsea multilateral well exhibited unexpected sand production and a tubing leak, leading to the well being shut in. The complete paper discusses the novel tools and techniques used to localize the tubing leak, identify the bore responsible for sand production, and provide relative sand quantification at differing flow rates. Well Background and History The well was drilled and completed as a subsea producer to be tied back to an existing floating production, storage, and offloading (FPSO) vessel by means of a subsea flowline. After drilling of the first lateral, the decision was taken not to complete it. A second lateral was then drilled and completed. The main and secondary bores were drilled into different zones of the reservoir. Both lower completions used standalone sand screens, autonomous inflow-control-device nozzles, and swell packers set in open hole. Each of the lower completions was fitted with a hydraulically actuated inflow control valve (ICV) for managing production flow from the reservoir zones, providing the ability to produce each leg independently or commingle them. The upper completion is equipped with two gas lift valves (GLV) to provide artificial lift, a chemical injection mandrel, and a surface-controlled subsea safety valve (SCSSV). After approximately 6 months of flowing the well, water cut was seen to increase and a series of “popping” events occurred in which productivity increased markedly for short periods. Significant quantities of sand soon began to accumulate in the FPSO topside facilities. Approximately 1.5 years after startup, well productivity decreased sharply over a few months while the water cut continued to increase. As the productivity continued to decline, the leak rates exhibited by the SCSSV and one GLV fell outside the acceptable criteria. The pressure responses indicated a high leak rate. The well was shut in pending diagnostic logging and repair of the leak. Sand-Source Investigation The subsea wellhead of this well was fitted with an acoustic sand detector, but this had only indicated minor amounts of solids in the flowstream over the producing lifetime of the well. An extensive investigation concluded that the makeup of the collected sand was most likely to have originated in the case study well and that the amounts involved were likely to have been a contributing factor in the loss of well integrity. Because the well was producing from two different branches, a probability existed that only one of these was suffering from sand production. The well completion was designed to allow independent control of the branches by use of ICVs, so an intervention to assess the status of each of the branches with respect to water and sand production was planned, with the additional objective of diagnosing the well-integrity failure.

Characterizing facies and porosity-permeability heterogeneity in a geothermal carbonate reservoir with the use of NMR-wireline logging data

If they are to be economically and technically sustainable, geothermal projects require the production of hot fluid at high flow rates over a 30-year thermal lifetime. The combined use of multiple logging tools in making petrophysical assessments of reservoir quality helps to optimize drilling in areas of high geothermal potential. The present paper focuses on four geothermal wells intercepting Middle Jurassic (Dogger) carbonate rocks of the Paris Basin where for the first time Nuclear Magnetic Resonance (NMR) log data have been successfully used to investigate reservoir porosity-permeability heterogeneities. A total of ten facies have been identified from recovered cuttings and cores and grouped into four facies associations along a schematic carbonate ramp profile. From the wells studied, four reservoir units exhibiting porosities exceeding 15% and permeabilities of up to 1 Darcy (D) were traced in the Calcaires de Comblanchien, the Oolithe Blanche and the Calcaires marneux à Pholadomyes formations. The well's sub-horizontal trajectory and well-logs correlations between two wells, made it possible a priori to identify porous and permeable layers extending over at least 500 m and up to 2000 m within the Bathonian reservoir, providing useful pointers for further 3D reservoir geomodeling. Permeabilities derived from well testing proved to be overestimated when compared with NMR-derived permeabilities, illustrating the upscaling problem that is invariably a challenge in carbonate systems. NMR can be combined with production logging tool (PLT), that provides data on the distribution and thickness of productive layers, to give indications for example about continuous permeability record along the geothermal wells or about the proportion of micro and macroporosities in rocks. Based on the geological classification derived from examination of cores and cuttings, four rock-types (including mean T2 pore-size distributions) have been identified and attributed to a given sedimentary facies and depositional environment by extending a clustering method to NMR log distributions from wells.

Geochemical Approaches Assist Production Allocation of Commingled Fluids

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 205130, “The Application of Petroleum Geochemical Methods to Production Allocation of Commingled Fluids,” by Richard Patience, Mark Bastow, and Martin Fowler, Applied Petroleum Technology, et al. The paper has not been peer reviewed. _ Geochemical-based methods for production monitoring and allocation are much lower-cost than use of production logging tools because no additional rig time or extra personnel are required at the well site. Additionally, no intervention to the production of hydrocarbons from a well is required, reducing operational risk. The complete paper summarizes these approaches and provides examples and describes a best practice that avoids a one-size-fits-all approach. Introduction Production allocation from petroleum geochemistry is defined here as the quantitative determination of the amount or portion of a commingled fluid to be assigned to two or more individual fluid sources at a particular moment in time based on fluid chemistry. It requires knowledge of the original chemical compositions of each of the fluids before mixing (referred to here as the “end members”) and the ability to identify statistically valid differences in their chemistries. The fluid may be oil, gas, or water. The concept is illustrated in Fig. 1a by mixing colors to represent the end members and commingled fluid. Production monitoring, in contrast, is the analysis of a time series of production fluids from the same source. This is demonstrated in Fig. 1b, where a change in chemistry can be observed between Days 60 and 100. Two data points at the same time are duplicates, proving that the change in chemistry is real and not an artifact. It is generally qualitative to semiquantitative in comparison with production allocation. Production allocation, therefore, is inherently more complex, in terms of both the sample requirements and data treatment. Allocation is the main focus of this paper. Allocation Sampling Strategies For a production allocation project, the three following distinct stages require samples: Stage 1: Can Contributing End Members Be Distinguished? In the initial stage, a determination must be made regarding whether end member reservoirs contributing to production can be distinguished based on their chemical composition. End Members From Conventional Plays. These typically are flowed samples from drillstem tests, bottomhole samples from wireline tools, or production tests, usually taken during the drilling of exploration or appraisal wells. Several issues must be considered when assessing the usefulness of such samples: - Are the end member samples representative of the reservoir as a whole? - Is the end member sample contaminated with organic compounds from drilling fluid? - When were the end members taken, how were they stored, and has there been significant alteration of the composition of the sample as a result?

Using core to reduce risk and deliver added business value throughout field life: a carbonate reservoir focus

Abstract The role of the subsurface team is to reduce technical risk and uncertainty associated with profile delivery, for both hydrocarbon production and the injection of water or gases, enabling confident reservoir management and investment decisions. Core is a key resource for delivering this objective, providing the only opportunity to directly observe and measure the reservoir rock. However, it is expensive to acquire and the decision to take new core should be clearly linked to a business objective. A combination of depositional and diagenetic factors can result in carbonate reservoirs being highly heterogeneous, making them a challenge to find and develop. Core studies can significantly improve understanding of the controls on heterogeneity and its distribution within the subsurface, but to maximize value, they should be fully integrated with wireline logs, seismic and production or test data to predict likely reservoir behaviour. For example, thin (<1 m) high or low permeability zones can dominate production yet remain very subtle or undetectable in wireline log or seismic data alone. During exploration and appraisal, sufficient data and knowledge are required to enable appraise/develop or walk-away decisions. Appropriate geological description of core material helps to establish original volumes in place, net-to-gross, depositional setting, age, reservoir architecture and large-scale flow zones. Core material can also help establish other key reservoir parameters such as saturation, reservoir fluids, seismic rock properties and geomechanical properties as well as influence decisions such as well design, development strategy and facility requirements. As a field is developed and production matures, reservoir behaviour may change and detail of the sedimentology, structure, diagenesis, baffles and thin heterolithic permeability zones may become more important. In carbonate reservoirs, this often requires the integration of existing legacy core or new core material and targeted surveillance data, such as injection and production logging tool (ILT/PLT) or saturation logs, to understand the stratigraphic, depositional and diagenetic controls on flow units and improve predictive capability. Moving a reservoir from natural depletion onto waterflood or enhanced oil recovery (EOR) may need more advanced core-based data from core flood experiments to deliver maximum value from the reservoir. New core material, or detailed review and new sampling of existing or analogue legacy core, may be required to understand complex rock–fluid interactions and the value that waterflood or EOR could bring to a development. To maximize the value and insights gained from core, it is essential to use it throughout a field's life. High quality description and a well-considered sampling regime should be carried out at the earliest opportunity to provide baseline data. However, periodically revisiting the core enables the entire subsurface team to keep testing hypotheses and refreshing models. Where there is no core material available in the field, analogue field core can be especially useful both to narrow uncertainty and explore possible alternative models. A multi-disciplinary approach integrating new data with core observations helps refine and improve predictions and can lead to the identification of significant additional opportunities as reservoir behaviour matures and field development progresses.

Evaluation of pore-throat structures of carbonate reservoirs based on petrophysical facies division

After complex geological transformation, such as sedimentation, diagenesis, and tectonic transformation, carbonate reservoirs have developed multiple reservoir spaces with significant heterogeneity and various pore-throat structures, including pores, vugs, and fractures. Due to these characteristics, many problems have been caused during the development of carbonate reservoirs, such as large differences between the initial production capacities of single wells and serious water channeling after injection, which have brought many challenges to the efficient development of carbonate reservoirs. Therefore, based on a reservoir evaluation method of petrophysical facies, this study classified and evaluated the pore-throat structures of Carboniferous carbonate reservoirs in the North Truwa oilfield of the Pre-Caspian Basin. Based on the data of the core, thin section, scanning electron microscope, high-pressure mercury injection, sedimentary facies, diagenetic facies, and the development of fractures and karst vugs, six reservoir petrophysical facies in the study area were classified and named, including the facies of favorable sedimentation-constructive diagenesis-fracture and vug, the facies of favorable sedimentation-constructive diagenesis-non-fracture or vug, the facies of favorable sedimentation-destructive diagenesis-fracture and vug, the facies of favorable sedimentation-destructive diagenesis-non-fracture or vug, the facies of unfavorable sedimentation-constructive diagenesis-non-fracture or vug, and the facies of unfavorable sedimentation-destructive diagenesis-non-fracture or vug. The recognition and division of diagenetic facies were based on the K-nearest neighbor. Four quantitative parameters were also selected to characterize the pore-throat structures, including displacement pressure (Pd), mercury removal efficiency (Em), median throat radius (R50), and sorting coefficient (Cs). Based on the principal component analysis, the classification and evaluation standards of pore-throat structures in different petrophysical facies were established. Combined with the flow profile measured by production logging tools, the relationship between different petrophysical facies and productions was also revealed. As a result, this study can provide suggestions for the adjustment strategy of water-driven production, which lays an important foundation for the fine development of carbonate reservoirs.

Integrated Diagenetic-Depositional Facies (IDDF) characterization and 3D geomodeling in carbonate reservoirs

Carbonate reservoirs are very prone to diagenetic modification of pre-existing fabrics. The process around the modification of pre-existing depositional fabrics is often interrelated with diagenetic phases that impact reservoir quality and distribution. Characterization and 3D modeling of these features have always been a challenge in the upstream industry. This paper outlines a novel workflow for characterizing and modeling the Integrated Diagenetic-Depositional Facies (IDDF) in carbonate reservoirs, from 1D IDDF classification and Neural Network (NN) estimation, to 2D IDDF trend and seismic-based probability region modeling, culminating with the 3D geo-cellular modeling processes. The workflow integrates several geoscience data sets including; linking of petrographic thin sections analyses with other scales of data from core descriptions, well-logs signatures, Routine Core Analyses (RCA), Production Logging Tool (PLT) inflow analyses, diagenetic proxies and depositional concepts. The IDDF workflow ties these features with 3D seismic attribute region extraction to benefit 3D geo-cellular property modeling. This workflow greatly improves reservoir quality prediction, 3D reservoir modeling and volume estimation.

Unlocking the Potential of Acid Stimulation in Volcanic Rocks: A Successful Case with Integrated Analysis in Minami-Nagaoka Gas Field, Japan

Summary Acid stimulation of volcanic formations is rarely documented in the literature. A recent study however suggested its potential effectiveness through a comprehensive laboratory/modeling analysis and documented substantial permeability enhancement by dissolution of carbonate-cemented fractures in the near-wellbore area to create wormhole-like high-permeability channels. The study also presented a brief description of successful field execution, although operational details and analysis of results were not presented. This work presents in detail the field case of a multistage acidizing treatment in the Minami-Nagaoka gas field, a volcanic reservoir, and demonstrates the effectiveness of acid stimulation with 10% formic acid for productivity enhancement. The selection of a target well relies on the abundance of cemented fractures along a well. The operational design considers multiple field/well characteristics, such as low permeability; long, perforated intervals; and high-temperature conditions. Effectiveness of acid stimulation is evaluated comprehensively and justified by the integration of real-time stimulation diagnostics using distributed temperature sensing (DTS), real-time surveillance of bottomhole key parameters obtained thanks to coiled-tubing (CT) fiber-optic downhole telemetry, pre-/post-acidizing pressure buildup (PBU) tests, and production logging tool (PLT) surveys. A multistage acidizing operation was executed, after completion of a step-rate test during which a pre-acidizing DTS survey was acquired. Eight stages of 10% formic acid injection and seven stages of degradable particulate diverter placement were pumped, followed by brine displacement and a post-acidizing DTS acquisition. In all the stages, acid injection decreased the bottomhole pressure while the use of diverter increased it (by hundreds of psi), thus indicating success in acid stimulation and diversion, respectively. The stimulation almost doubled the gas flow rate just after the operation, and 10 months after the operation, the gas rate is still 1.5 times higher than before intervening. Pre-/post-acidizing PBU tests suggested a substantial reduction of the skin from 1.50 to −1.91. DTS surveying identified one major and three minor fluid-intake intervals through stimulation/diversion, and integrated analysis with PLTs revealed that the substantial improvement in gas rate was primarily coming from a narrow zone located within the major intake interval, where resistive fractures are abundant. The current case demonstrates the effectiveness of 10% formic acid for the stimulation of rocks with carbonate-cemented fractures, which was also proposed by the former study. It also shows that there is still room for further optimization in the operational design. This paper provides insights on acid stimulation in volcanic rocks and highlights its effectiveness through the analysis of a series of data sets. Readers may obtain knowledge on acidizing design, the evaluation of its effectiveness, and the interpretation of results, with lessons learned through job execution. The study will also serve as a reference to evaluate the potential of acid stimulation for the development of other volcanic reservoirs.

Performance evaluation of boosting machine learning algorithms for lithofacies classification in heterogeneous carbonate reservoirs

Lithofacies classification from well logs recorded through heterogeneous carbonate reservoirs helps to improve reservoir discrimination with respect to fluid flow and storage capabilities. A novel technique is developed to classify carbonate lithofacies with the assistance of boosting algorithms for a well drilled into the large Majnoon oil and gas field of southern Iraq. Five boosting machine learning algorithms: Logistic Boosting Regression (LogitBoost), Generalized Boosting Modeling (GBM), Extreme Gradient Boosting (XGBoost), Adaptive Boosting Model (AdaBoost), and K-nearest neighbor (KNN) were comparatively implemented to attain the most realistic lithofacies predictions. Data from available cores provide actual lithofacies determination. Additionally, seven standard well logs recorded provide continuous additional information across the complete reservoir section. Random sub-sampling of the well-log dataset was used to train and test the models. Confusion matrices of the results provided Total Percent Correct (TPC) accuracy measures for LogitBoost, GBM, XGBoost, AdaBoost, and KNN with respect to the entire dataset of 97.65%, 96.99%, 97.74%, 97.74%, and 96.74%, respectively, and with respect to the validation subsets TPC was 94%, 96%, 98%, 91%, and 96%, respectively. The XGBoost provided more accurate lithofacies classification than the other five boosting algorithms with respect to the predictions generated for both the entire dataset and testing subset. The lithofacies predictions were then compared with poro-perm interpretations from the Nuclear Magnetic Resonance (NMR) log and oil rate from the Production Logging Tool (PLT). Rudist-rich and argillaceous lithofacies display lower porosity and permeability, respectively. The Rudist-rich lithotype is associated with high-production-rate zones, whereas the argillaceous facies is associated with low-production-rate zones. The boosting machine learning workflow developed efficiently provides accurate lithofacies classification with reduced uncertainty in carbonate lithofacies determinations. The entire workflow was fully implemented and visualized using open-source R computer codes. These codes have the potential to be generalized for the application of facies classification to other clastic and carbonate reservoirs in oil and gas fields.

Optimization of the PLT complex for the problems of the inflow profile estimate in low-rate gas wells on the example of the Berezovskaya suite

Currently, more and more attention is being paid to hard-to-recover reserves characterized by low flow rates. And one of the problematic issues in the process of studying them is the correct determination of the inflow profile by conducting production logging tool (PLT). In this regard, there is a need to increase the information content of the PLT in the conditions of gas reservoirs with a low flow rate, where the Berezovskaya suite is an actual research area. In this paper, a new PLT scheme is proposed, based on the actual PLT scheme, which will allow more reliable determination of operating intervals in low-rate gas-saturated reservoirs.

New Logging Tool for Enhanced Oil Recovery and Gas Storage Monitoring Applications

There is currently no production logging tool that can analyze in-situ gas composition in wells that intersect more than one pay zone. In high-value gas wells, zonal isolation is useful for enhanced oil recovery (EOR) applications such as injection monitoring, pressure maintenance, and identification of layers that contain low-calorific-value gas. To unlock these key applications related to gas reservoir management, a new production logging tool was developed that introduces downhole gas composition analysis to the production logging tool string. The tool does not require a formation seal and so can log continuously or at a station. For gas field applications with pressures above 3,000 psi, the estimated mole fraction errors in continuous logging mode are ~2% for methane and ~1% for ethane, propane, nitrogen, and carbon dioxide. In formations with lower pressures, station logs can achieve mole fraction errors < 1% for all components.

First Worldwide Slim Coiled-Tubing Logging Tractor Deployment

Summary Successful reservoir surveillance and production monitoring is a key component for effectively managing any field production strategy. For production logging in openhole horizontal extended reach wells (ERWs), the challenges are formidable and extensive; logging these extreme lengths in a cased hole would be difficult enough but is considerably exaggerated in the openhole condition. A coiled-tubing (CT) logging run in open hole must also contend with increased frictional forces, high dogleg severity, a quicker onset of helical buckling, and early lockup. The challenge of effectively logging these ERWs is further complicated by constraints in the completion where electrical submersible pumps (ESPs) are installed, including a 2.4-in. bypass section. Although hydraulically powered CT tractors already existed, a slim CT tractor with real-time logging capabilities was not available in the market. In partnership with a specialist CT tractor manufacturer, a slim logging CT tractor was designed and built to meet the exceptional demands of pulling the CT to target depth (TD). The tractor is 100% hydraulically powered, with no electrical power, allowing for uninterrupted logging during tractoring. The tractor is powered by the differential pressure from the bore of the CT to the wellbore and is operated by a preset pump rate from surface. Developed to improve the low coverage in openhole ERW logging jobs, the tractor underwent extensive factory testing before being deployed to the field. The tractor was rigged up on location with the production logging tool and run in hole (RIH). Once the CT locked up, the tractor was activated and pulled the coil to cover more than 90% of the openhole section, delivering a pulling force of up to 3,200 lbf. Real-time production logging was conducted simultaneously with the tractor activation; flowing and shut-in passes were completed to successfully capture the zonal inflow profile. Real-time logging with the tractor is logistically efficient and allows instantaneous decision making to repeat passes for improved data quality. The new slim logging tractor (SLT) is the world’s slimmest and most compact and is the first CT tractor of its kind to enable production logging operations in openhole horizontal ERWs. The importance of the ability to successfully log these ERWs cannot be overstated; reservoir simulations and management decisions are only as good as the quality of data available. Some of the advantages of drilling ERWs, such as increased reservoir contact, reduced footprint, and fewer wells drilled, will be lost if sufficient reservoir surveillance cannot be achieved. To maximize the benefits of ERWs, creative solutions and innovative designs must be developed continually to push the boundaries further.

Integrated Fracture Characterization of Thamama Reservoirs in Abu Dhabi Oil Field, United Arab Emirates

Summary Volumetric maximum curvature attribute computed from 3D ocean bottom cable (OBC) seismic data, production logging tool (PLT), inorganic chemical tracer data, and fractures observed from core and full-bore formation microimager (FMI) logs were integrated to characterize fractured carbonate reservoirs of an offshore oil field in Abu Dhabi, United Arab Emirates (UAE). The extracted maximum curvature anomalies are predominantly orientated in NNE-SSW and NE-SW, a trend perpendicular to the dominant fault direction in the oil field and similar to the dominant strike directions of fractures measured from core data and FMI logs. Because the fracture strike directions of well data mimic the strike directions of curvature anomalies at corresponding reservoir levels, we interpreted the maximum curvature anomalies to represent dilatational fractured zones or fracture corridors. Integration of dynamic data, such as PLT and chemical tracers, and maximum curvature anomalies demonstrate that the inferred fracture zones can determine water breakthroughs as well as inter- and intrareservoir communications. As a result, this study highlights possible fracture zones and their internal architecture, as well as their potential flow capabilities. These results play a key role in reservoir management and monitoring of water movement through structural pathways.