Germik, a mature heavy oil field in Southeast Turkey, has been producing for more than 60 years with a significant decline in pressure and oil production. To predict future performance of this reservoir and explore possible enhanced oil recovery (EOR) scenarios for a better pressure maintenance and improved recovery, generation of a representative dynamic model is required. To address this need, an integrated approach is presented herein for characterization, modeling and history matching of the highly heterogeneous, naturally fractured carbonate reservoir spanning a long production history. Hydraulic flow unit (HFU) determination is adopted instead of the lithofacies model, not only to introduce more complexity for representing the variances among flow units, but also to establish a higher correlation between porosity and permeability. By means of artificial intelligence (AI), existing wireline logs are used to delineate HFUs in uncored intervals and wells, which is then distributed to the model through stochastic geostatistical methods. A permeability model is subsequently built based on the spatial distribution of HFUs, and different sets of capillary pressures and relative permeability curves are incorporated for each rock type. The dynamic model is calibrated against the historical production and pressure data through assisted history matching. Uncertain parameters that have the largest impact on the quality of the history match are oil-water contact, aquifer size and strength, horizontal permeability, ratio of vertical to horizontal permeability, capillary pressure and relative permeability curves, which are efficiently and systematically optimized through evolution strategy. Identification and distribution of the hydraulic units complemented with artificial neural networks (ANN) provide a better description of flow zones and a higher confidence permeability model. This reduces uncertainties associated with reservoir characterization and facilitates calibration of the dynamic model. Results obtained from the study show that the history matched simulation model may be used with confidence for testing and optimizing future EOR schemes. This paper brings a novel approach to permeability and HFU determination based on artificial intelligence, which is especially helpful for addressing uncertainties inherent in highly complex, heterogeneous carbonate reservoirs with limited data. The adopted technique facilitates the calibration of the dynamic model and improves the quality of the history match by providing a better reservoir description through flow unit distinction.

Dynamic saturation distribution of fluids in oil reservoirs is arguably the most important piece of information petroleum engineers and geophysicists need. It allows them to better characterize oil fields, choose right enhanced oil recovery techniques and make accurate recovery forecasts. The main objective of the present paper is to develop and test a novel non-intrusive technology that enables real time in-situ monitoring of fluid saturations in porous media during immiscible floods. To achieve this goal we designed, constructed and commissioned a high pressure (up to 25MPa) and temperature (up to 200°C) core-holder with an antenna that allows for low power electromagnetic sweeps in the radio frequency range. A novel inversion algorithm was created and incorporated with our core-holder-pump system that enables dynamic acquisition of the oil and water saturations. Experiments were conducted through sand packs saturated with water and then displaced with oils of varying viscosity (drainage) followed by water flooding (imbibition). Reflection and transmission coefficients in the frequency domain were measured while flooding using a commercial vector network analyzer connected to the core holder. Recorded frequency data was processed with the novel high-resolution inversion technique to obtain impulse reflection and transmission responses in the time domain. These responses were further normalized to dynamically track the water-oil volumetric saturations within the porous media. Every displacement experiment has been performed in both vertical and horizontal positions to emulate water-oil override and underride scenarios. Material balance calculations were performed to validate fluid saturation profiles for all imbibition and drainage experiments every 5 % of the pore volume of the fluids injected. Frequency domain reflection and transmission electromagnetic responses were measured every 1 % of the fluid injected. Material balance was used to validate the measured saturation profiles. The goodness of fit was calculated between these two independent measurements for every flood experiment performed. The mean-square error was calculated to be around 1.26% of the total pore volume on average. Late breakthroughs and piston-like displacement were observed in the floods with favorable mobility ratios. In contrast, much earlier breakthroughs have been registered in all the experiments with unfavorable mobility ratios due to fingering. All our observations are in agreement with the current theory of immiscible displacement in porous media. The novel automated system paired with the inversion algorithm were developed to allow for virtually real time monitoring of the fluid saturations during imbibition and drainage displacement cycles. Our technology is shown to be a promising candidate to compliment resistive logging measurements in the field.

To unlock unconventional reservoirs for optimum production, maximum contact with the reservoir is required; however, excessively dense well placement and hydraulic fractures interconnection is a source of well-to-well interaction which impairs production significantly. The first step to have successful and effective well completion is to understand the characteristics of the hydraulic fractures and how they propagate in reservoir. This paper demonstrates an integrated approach with a field example in the Montney formation for how modern modeling techniques were used to understand and optimize hydraulic fracture parameters in unconventional reservoir. Advanced logs from vertical wells and 3D-seismic were used to build an integrated geological model. Lamination index analysis was performed, using borehole imagery data to account for interaction of hydraulic fracture with vertically segregated rock fabric and to provide additional control on hydraulic fracture height growth during modeling process. A non-uniform Discrete-Fracture-Network (DFN) model was constructed. 3D-geo-mechanical model was built and initialized, using sonic log and seismic data. Fluid friction and leak-off was calibrated, using treatment pressure and DFIT data. Hydraulic fracture modeling was done for pad consists of 6 horizontal wells with multi-stage fracturing treatments, by utilizing actual pumped schedules and calibrating it against microseismic data. High-stress anisotropy led to planar hydraulic fractures despite presence of natural fractures in area. Fracturing sequence, i.e., effect of stress shadow, is seen to have major impact on hydraulic fracture geometry and propped surface area. Heatmaps were generated to estimate average stimulated and propped rock volume in section. It was also observed that rock fabrics, i.e., natural fracture and lamination has considerable impact on propagation of hydraulic fracture. Multiple realizations of natural fracture and lamination distribution were generated and used as an input in modeling process. High resolution unstructured simulation grids were generated to capture fracture dimensions and conductivities, as well as track propped and unpropped regions in stimulation network. Dynamic model was constructed and calibrated against historical production data. History matched model was then used as predictive tool for pad development optimization and to evaluate parent-child interaction in depleted environment.

Umm Ghudair Field is one of the major oil producing fields in West Kuwait. Oil was discovered in 1962 in the Lower Cretaceous Minagish Oolite Formation and more than 200 wells have been drilled to exploit this reservoir since then. Stratigraphically, the formation is defined by three units; Lower, Middle and Upper. The lower and upper units are considered non-reservoirs, while the middle one is hydrocarbon bearing. However, because of the continuous production over the past 50 years, the filed started to show a variable rise in its oil water contact (OWC). Consequently, this uncertain OWC rise has impacted the planning and production of the newly drilled wells (deviated and horizontal). Several recently drilled wells showed water breakthrough much earlier than expected. To address this challenge and with an attempt to proactively predict the current OWC depth in the new wells to be drilled, Kuwait Oil Company (KOC) decided to try the new High Definition Reservoir-Mapping-While-Drilling (HD-RMWD) technology in one of the horizontal well in their field. The objective was to assess the potential of the technology in detecting and mapping the current OWC while landing the well in the target. Due to the ultra-deep detection range of the technology (in excess of 200 ft), the landing point could be adjusted proactively and early enough to accommodate any unexpected OWC depth changes in the field.

Hydraulic proppant fracturing is one of the most effective tools to optimize production in the mature, low- permeability reservoirs found in the Pannonian Basin in Central Europe. Fracturing can effectively enhance production by improving reservoir contact, but for wells already producing with high water cut, even a small fracture extension into a water-bearing or "wet" zone offsets the gains in hydrocarbon production. Fracture geometry control (FGC) techniques limit increases in water cut, which is one of the greatest challenges to extending economic production and maximizing ultimate recovery for mature wells. Artificial barrier placement and proppant channel fracturing were proven to improve hydrocarbon production while fracturing stimulation targets adjacent to high water saturation intervals. The pilot included candidates in thin, low-permeability sandstone reservoirs, located within 5 to 10 m of wet intervals. An integrated engineering approach to fracture height growth was applied, including a new proppant transport model to predict fracture geometry improvement using the FGC solution. The FGC solution consisted of injection of an engineered particulate mixture designed to bridge at the fracture edges and arrest height growth. Additionally, the bridging mixture provided reduced conductivity and acted as a fracture flow restriction for water. The FGC solution was also combined with channel fracturing in some trials as an attempt to reduce net pressure development, minimize the risk of height growth and improve fracture quality in the low-permeability reservoirs. The new engineering approach, incorporating the new solids transport simulator, enabled the successful implementation of the FGC technique in the pilot candidates. Fracture height control was achieved in absence of good geological barriers. The benefits of this new approach are supported by a consistent improvement in hydrocarbon production without an increase in water cut. In field A, the combination of FGC and channel fracturing resulted in additional production when compared to wells where only FGC was implemented. Evaluation of this pilot included a comparison with offset wells stimulated without this technique when a water cut increase was always observed in the field A. This paper describes the first implementation of the complex technology and engineering solution to control fracture height for conventional wells in the Pannonian Basin. For the first time, the mixture of solids was modeled directly, and the influence on fracture geometry and production results is shown. The cases are of significant interest because of the global challenge of maximizing recovery from mature reservoirs with nearby water hazards. The application of a full engineering process for the design, placement, and evaluation of the fracture height control treatments provides an improved degree of confidence that such operations can result successful production optimization. The workflow as presented and applied is an effective tool to reduce risk of high water production when fracturing close to water contacts.

Reservoir development decisions strongly depend on our understanding on reservoir heterogeneity, which is often subject to sparse and conflicting data, interpretational bias and constraints imposed by the modelling assumptions. The work tackles a challenging task of accurately and quickly identifying and describing uncertainty in the spatial distribution of reservoir heterogeneity derived from geological well data and with respect to a geological concept. We propose a metric based machine-learning approach to identify and describe spatial trends in reservoir heterogeneity/facies property distribution using wireline and production data. We demonstrate how the proposed method can help to partition reservoir heterogeneity and discover and verify spatial trends for a real mature producing field in the Western Siberia. The obtained clustering of reservoir facies based on the wireline logs (alpha-SP) demonstrated a good agreement with the reservoir zonation based on manual log interpretation and the geological concept. Clustering based on individual well production profiles has confirmed the reservoir partitioning and matched some of the reservoir features aligned with the prevailing geological concept. The outcome of the proposed method helps to improve the facies distribution model by integrating the discovered spatial trends into a geostatistical model and account for uncertainty in the depositional scenario that is difficult to quantify based on manual interpretation.

Innovative reservoir seismic characterization technologies, with massive integration of Seismic and Petrophysical data, were applied for the first time, almost ten years ago, to a green field since the appraisal phase. This seismic driven static model has been continuously kept alive during development and production, effectively supporting application of innovative technologies, operations and business decision processes. Main object of this paper is to present a global overview of how different methodologies were implemented and tuned while the model evolved, taking advantages of lessons learned to improve technical knowledge and set up new opportunities. The initial model, based on five wells, was adopted to characterize the reservoir, with a robust link between lithology, elastic and dynamic properties. The innovative Petro-Elastic facies characterization, tuned at field scale for the next development phase, proved to be valid during the drilling campaign of more than twenty HA-HZ wells, with only minor adjustments required to propagate the model. An automated workflow for geostatistical simulations conditioned by seismic probability cubes of facies and petrophysical properties and multi-scenario risk analysis, including depth conversion and well calibration of seismic properties, generated Static and Dynamic models ready to be approached with a Computer Assisted History Match (CAHM)/ Ensemble based Methods. Properties distribution did not require new seismic inversion meanwhile updating the model, confirming the predictability of seismic in terms of average properties and the consistency of Rock Physics Model and Petrophysical characterization. To drill horizontal wells, geosteering activities were assessed by generating fine scale pre-job sector models. Optimization of well trajectories was not based only on seismic but on posterior probability of facies and petrophysical properties generated by a dedicated workflow. During drilling, real time integration of seismic inversion, wellbore data, and Ultra-Deep Azimuthal EM Reservoir Mapping allowed to effectively support well placement, providing real time stratigraphic interpretation of drilled sequences. The automated workflow permits now to investigate a wide distribution of realizations converging on a subset whose reservoir dynamic simulation are in agreement with the first years of production. The model represented a chance to implement approaches and workflows deployed in our reservoir department and now applied in top projects as well as in the day by day activities and still it is a platform to test new approaches and available technologies. Single innovative items have been object of more than twelve publications or conference presentations. Ten years later, we can assert that multidisciplinary integration and continuous cooperation between the subsidiary, in charge of operations, and the HQ was the key for the successful field characterization and development. For the future, this model could be a platform to test CAHM/ Ensemble based technology integrating also future 4D seismic data thanks to the initial tuned Petro Elastic facies model.

High angle S-shaped and high displacement L-shaped well profiles are preferred now-a-days in Balimara field located in the northeast region of India. Main targets are the deep Clastic reservoirs of Oligocene age. Major events reported are while drilling against dipping formations with differential stuck pipe situations with variety of drilling complications in the unstable formations owing to shales in Tipam sandstone and thin sections of coal and shale alteration in oil bearing Barail sandstone formation. The substantial risk of wellbore instability in accessing the reservoirs with lateral variation in pore pressure threatened the commercial success of the project. This paper elaborates how geomechanical information along with BHA design and chemicals was integrated into the decision-making process during well design and drilling operations to avoid wellbore instability issues. Wellbore stability analysis through Mechanical Earth Model was conducted using estimated state of stress and mechanical properties of the overburden and reservoirs. The model incorporated data from several sources including geophysical logs, leak-off tests, advanced sonic far field profile and drilling records collected from the earlier wells. Examination of the deviated well bore profiles suggested occurrence of ledges due to lower mud weight and improper drilling parameters while drilling alternate layers of sand, shale and coal in Barail formation. Horizontal stress contrast increases in Barail formation supporting the need of higher mud weight with increased well deviation towards specific azimuth. The integrated geomechanical analysis provided key information: The 9 5/8" casing shoe should be set at shale layer of Tipam Bottom to isolate upper differential sticking prone sandstone layers with Barail Argillaceous sequence. This will help to drill 12.25-inch hole with 9.6 ppg-9.8 ppg only. Shale layers at Tipam bottom require 10.0-10.5 ppg, while Barail shale requires 10.5 ppg-11.0 ppg for vertical well. When the well deviation increases up to 30deg, mud weight requirement rises to 11.2 ppg-11.8 ppg. Based on analysis, the mud weight at the start of 8.5inch section was raised sufficiently to 10.5 ppg to avoid the hole collapse experienced in the earlier lower angle wells. Later, continuous review of torque and drag along with cutting analysis helped to raise mud weight up to 11.0 ppg till well TD. As a result, lower UCS shale and coal layers are drilled with minimal shear failure and improved hole condition. However, changes to the mud system were needed to limit fluid loss and avoid differential sticking across the sandstone. For deviated section, rotary BHA has been used to improve hole trajectory vs. planned with lesser ledges. Downhole hydraulics has been maintained with proper flow rate and rpm to main hole cleaning. The new well engineered with the integrated geomechanics information has been drilled from surface to extended TD while saving 15 rig days.

Objective/Scope: Advanced geo-navigation technique in multilateral wells is currently being used to optimize oil production from a number of reservoir zones in Mauddud formation in the ongoing development of Sabriyah oil field. Multilateral wells generally help reduce cost of hydrocarbon production and are known to perform better than single horizontal wells. However, the application of appropriate geo-navigation strategy and downhole logging-while-drilling (LWD) technologies to achieving maximum reservoir exposure is key to production outcomes. Well-ML was planned as a multilateral well with two horizontal drain sections LAT-0 and LAT-1, each targeting multiple reservoir zones MaB, MaC and MaD in Mauddud. The main objectives of the two horizontals was to place the wellbores in the more porous and less dense sections of the targeted reservoir zones, achieving 30 - 45%, 10 -15% and 50 - 60% of reservoir footages in MaB, MaC and MaD respectively. The variation in the reservoir depositional facies and structural uncertainties due to the presence of a major fault pose geosteering challenges, also risking not achieving the require reservoir footages in the targeted Mauddud reservoir zones. Methods, Procedures, Process: A geo-navigation model was created using offset well gamma ray, resistivity, bulk density and neutron measurements. Petrophysical evaluation of simulated curves from LWD tool responses along the wellbore trajectory was used to optimize the location of the horizontal wells in the targeted reservoir zones. Selection of BHA tool was based on the degree to which simulated curves from specific LWD tools displayed identifiable response to variation in reservoir facies and structural character. The implemented BHA comprised of the rotary steerable system, azimuthal deep resistivity "distance-to-boundary" technology, and the near bit density-porosity. Results, Observations, Conclusions: The enhanced geo-navigation technique of integrating the near-bit-density-porosity and the azimuthal deep resistivity distance-to-boundary tools played a major role in navigating the wellbore within the sweetest spot of the multiple reservoir zones with confidence. Percentage footage achieved in MaB-MaC-MaD was 49%- 14%-37% in LAT-0 and 34%-17%-49% in LAT-1. The positioning of the density/porosity sensors close to the drill bit reduced the reaction time to mitigate the challenges posed by abrupt changes in reservoir density/porosity characters and allowed for an earlier estimation of reservoir structural dips, particularly in MaC zone where there was poor azimuthal sensitivity in the deep resistivity measurements. The successful and continuous real-time geo-navigation operation resulted in an optimized production outcome that is 3 times the production from single horizontal producer recorded in the same multiple reservoir zones. Novel/Additive Information: Enhanced geo-navigation technique in multilateral well targeting multiple reservoir zones.

Evaluation of reservoir drive mechanisms is an important part of the field development planning process as it underpins recovery and defines project scope. Optimization of project scope (and resulting CAPEX) and the associated recoverable resource requires understanding of the natural reservoir energy and contribution of Improved Oil Recovery techniques such as water injection. This paper describes the evaluation of compaction drive for deep water fields for a development screening study. Pore volume compressibility has been characterized based on field burial depth, core analysis, tidal analysis and log data. Integration of this data provides a valuable knowledge base for regional screening and to bridge data gaps by enabling the use of more readily available log data for fields where a specific core laboratory test is not available. The primary source of information for pore volume compressibility is the laboratory testing on core. For the three fields included in the development screening study, only two have core testing results available for PV compressibility. A comprehensive analysis is undertaken to verify the core test results and to deduce the expected range of PV compressibility for the third field. The connected volume of the field (oil and aquifer zones) is an essential consideration for compaction drive. This is illustrated with material balance analyses of fields with limited vs significant aquifer support and implications on recoverable resource. Uniaxial tests on core samples are used to quantify static PV compressibility but these measurements are not available for all reservoirs. The effectiveness of establishing analogue trends and correlations for the characterization of PV compressibility is also demonstrated. Burial depth can be an initial indicator but may not be valid in all cases and an example of a geologically uplifted field is considered to help illustrate this. Reservoir pressure response to sea tide loading gives an indication of dynamic pore volume compressibility. The P wave modulus derived from sonic and density log data is shown to be very effective for the characterization. Even if a field is proved to have high pore volume compressibility, sufficient connected volume is required to benefit from the compaction drive and achieve sufficient recovery. Connected volume for the three fields included for the screening study is evaluated with aquifer mapping, comparison of pressure gradients with regional trends and consideration of potential barriers including faults and heavy oil at the oil water contact which is observed for one of the fields. The implications of these observations for field development planning are reviewed.

A high risk of suboptimal well placement exists in new field development where seismic uncertainty can be great. Recent ultradeep resistivity measurement developments provide great benefits for identifying and optimizing the well path position within a given stratigraphic sequence. This paper presents a case study in which an operator planned to place wells 10 m TVD below the reservoir top because of seismic uncertainty of the top reservoir pick. To help mitigate this subsurface risk, the field development plan required real-time well placement optimization, using both standard formation evaluation data and an ultradeep azimuthal resistivity service. In this case-history, the ultradeep inversion canvases could be used to identify the well path position within the reservoir, as well as provide sufficient confidence to steer the well closer to the reservoir top than originally planned. Multiple geological models, created from nearby offset wells and seismic grids, represented the expected seismic uncertainty of 5 to 15 m TVD. To identify the optimal measurement setup for real-time operations, resistivity modelling illustrated the effect of frequency and spacing on the data, producing multiple inversions for each geological scenario. After drilling began, real-time inversions for the ultradeep resistivity data were initially qualified using standard formation evaluation data, including both deep azimuthal resistivity and azimuthal density images. Multiple inversion canvases from various spacings and frequencies identified several formation features, including distances to the top and base of the reservoir. The quantified uncertainty of these results assisted in the evaluation of the inversion quality. When close to the reservoir top, the wellbore position indicated in the ultradeep inversion canvases matched the interpretation from the conventional logs, which provided increased confidence in the inversion canvas results at distances farther away. This enhanced reservoir knowledge enabled the operator to progressively raise the well path to 5 and to 2 m TVD from the reservoir top. Except for strategic geosteering decisions based on expected faults positions from the seismic data, the operator made most well-placement decisions, across multiple wells, using ultradeep resistivity data. The high data quality and close collaboration within the subsurface team quickly led to high confidence in the inversion results. Integrating the full suite of available data, from shallow to ultradeep measurements in a comprehensive interpretation, provided better reservoir understanding, resulting in optimal well placement. This paper presents formation evaluation results used within an integrated well-placement optimization service from a new field development. The integrated data qualified the results for an ultradeep resistivity tool. Confidence in the tool results enabled the operator to place wells much closer to the reservoir top than initially planned, in an area of seismic uncertainty.

Mud gas data from drilling operations provide the very first indication of the presence of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties from mud gas data, because it would provide knowledge of the reservoir fluid properties in an early stage, continuously for all reservoir zones, and at low costs. Previous efforts reported in the literature did not lead to a reliable method for quantitative prediction of the reservoir fluid properties from mud gas data. In this paper, we propose a novel approach based on machine learning which enables us to predict gas oil ratio (GOR) from advanced mud gas (AMG) data. The current work is based on a previous successful pilot in unconventional (shale) reservoirs. Our aim is to extend the results of the pilot study to conventional reservoirs. In general, prediction of reservoir fluid properties is more challenging for conventional reservoirs than for unconventional reservoirs, due to the complexity of petroleum systems in conventional reservoirs. Instead of building a model directly from AMG data, we trained a machine learning model using a well-established reservoir fluid database with more than 2000 PVT samples. After thorough investigation of compositional similarity between PVT samples and AMG data, we applied the model developed from PVT samples to AMG data. The predicted GORs from AMG data were compared with GOR measurements from corresponding PVT samples to assess the accuracy of the GOR predictions. The results from 22 wells with both AMG data and corresponding PVT samples show large agreement between prediction vs. measurement. The accuracy of the predictive model is much higher than previous results reported in the literature. In addition, a Quality Check (QC) metric was developed to efficiently flag low-quality AMG data. The QC metric is vital to give confidence level for GOR prediction based on AMG data when PVT samples are not available. The study confirms that AMG data can be used as a new data source to quantitatively predict continuous reservoir fluid properties in the drilling phase. The method can be used to optimize wireline operations and for some cases, it provides a unique opportunity to acquire reservoir fluid data when conventional fluid sampling or use of wireline tools is not possible. After high-quality PVT data becomes available in the wireline logging phase, the continuous GOR prediction can be further improved and used to determine reservoir fluid gradient and reservoir compartmentalization.

The initial high cost of exploitation of the sustained, increasingly growing development of unconventional resources in Argentina has resulted in concentrating all efforts to increase well productivity while reducing construction and completion costs. The optimization of hydraulic fracture (HF) treatments is vitally important. It is the primary strategy used to achieve an optimal reservoir drainage area, consequently characterizing the fracture geometry, including the height, for the continuous improvement of HF treatment and planning. Several types of technologies and methodologies are used to estimate fracture height during and after a hydraulic stimulation treatment. These technologies can provide information about the fracture geometry and extension in the near-wellbore (NWB) and far-field areas. The determination of a reliable correlation between those methodologies represents a challenge as a result of formation complexity, heterogeneity, and limitations of evaluation technologies. It is well-known that some areas in the Vaca Muerta formation contain layers that can act as fracture barriers and are responsible for fracture containment. This paper presents a fast and simple methodology that uses conventional well logs [gamma ray (GR), sonic, and density] from pilot wells to identify potential fracture barriers. This approach establishes a means to evaluate the degree to which the rock will have the ability to control fracture height growth. This methodology was determined useful for planning perforation intervals or clusters placement, particularly in those formations with stress profile showing reduced stress contrast and, when complemented with geological information, this method also provides useful information for horizontal well trajectory. Case studies are provided to illustrate examples of the proposed fracture barrier index (FBI) being calibrated or compared to other fracture height assessment. Additionally, the benefits of adding this new approach to current methodologies and technologies to aid completion design optimization and decision making is discussed.

Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) reckons on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability and hydrocarbon saturation still rely on model calibration using core measurements. Furthermore, assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include (a) developing a new multiphysics workflow to simultaneously quantify rock fabric features (e.g., porosity, tortuosity, and effective throat size) and hydrocarbon saturation from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements, (b) introducing rock physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure, and (c) validating the reliability of the new workflow in pore- and core-scale domains. To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid substitution algorithm to estimate the T 2 distribution corresponding to fully water-saturated rocks from the interpretation of NMR measurements. We use the estimated T 2 -distribution for assessment of porosity, pore-size distribution, and effective pore-body size. Then, we develop a new physically meaningful resistivity model and apply it to obtain the constriction factor and, consequently, throat-size distribution from interpretation of resistivity measurements. Finally, throat-size distribution, porosity, and tortuosity are used to calculate directional permeability and saturation-dependent capillary pressure. We test the reliability of the new multiphysics workflow in core- and pore-scale domains on rock samples at different water saturation levels. The introduced multiphysics workflow provides accurate description of the pore structure and fluid distribution in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. Finally, since the new workflow relies on fundamental rock physics principles, hydrocarbon saturation, permeability, and saturation-dependent capillary pressure can be estimated from well-logs with minimum calibration efforts, which is another unique contribution of this work.

The document presents a consistent method to build 3D Mechanical Earth Models (3D MEM). It is based on a rock physics study to derive field specific correlations between mechanical properties and interpreted petrophysical quantities. The 3D MEMs built using this methodology yield robustness and consistency when matching to the measured minimum stress. They also display good predictive capabilities making them valuable for operational design. This method consists of conducting a preliminary rock physics study in order to obtain correlations between the mechanical properties (elastic moduli and strength), of the various formations that are considered, and basic interpreted quantities which are readily available in most 3D geological models (porosity or mineralogy). The correlations are used to build a 3D MEM which is consistent with both the 3D geological model and the 1D geomechanical interpretation. It is also possible to extend the correlations by linking raw log data to rock mechanical properties. The model was tested against field case study to verify its predictiveness. Minimum stresses calculated by the 3D MEM matched well to the measured values obtained from mini-frac tests performed at various locations. Ultimately it permits to better forecast the material properties (in 3D) as well as the effective stress tensor (in 4D). The 3D MEMs were used to evaluate the risks for infill drilling, and for completion purposes. Performing this type of preliminary rock physics study has a number of benefits. Firstly, to help identify which logging suite should be run to characterize the geomechanical properties of a given formation, and secondly it can be used to derive correlations between raw log data and geomechanical properties. These correlations can be applied during operations for real time decision making purposes when there is not yet a petrophysical interpretation available. The novelty of the method introduced lies in the systematic and coherent integration of data to build a consistent geomechanical model (3D or 1D), that exhibits a robust predictive capability and shows the value of 3D MEM for the design of drilling and completion operations.

The paper illustrates systems and procedures recently adopted in Italy for the collection and recording of relevant drilling data, in the light of the requirements of Directive 2013/30/EU, elaborated and enforced following the 2010 Deepwater Horizon disaster. Thanks to the increased environmental consciousness of institutions, industry and people, worldwide environmental policies more and more require a rigorous protection of the environment. The Directive 2013/30/EU on the safety of offshore oil and gas operations introduced strict requirements for the protection of both people and the environment, that are the targets which could be involved and seriously damaged by incidents occurring at offshore installations. Today, the Italian law requires Operators to set up an information and communication technology system that guarantees the integrity, availability and non-repudiation of drilling and drilling fluids parameters recorded in real time aboard drilling vessels and offshore platforms, while respecting the principles of confidentiality and responsibility of the data, under all conditions. Oil companies operating in the Italian offshore implemented hardware and software systems that can be described as "Virtual Black Boxes". These are data management systems coupled to the Mud Logging Units of offshore drilling rigs, which allow the quasi-real time transmission of a subset of drilling parameters to a number of onshore data storage sites and their integral and safe recording on dedicated servers. The redundancy of information is ensured by managing multiple servers owned by the Operator and the mud logging Contractor. Normally, these servers are hosted at the Operators' headquarters and at Contractors' data storage centers. Data visualization is possible thanks to the use of special software, developed by Contractors and made available to Operators. Data acquisition, transmission and storage protocols are shared with the Italian competent Authority. These systems are already operative in the Italian offshore, even though studies are under way to enhance the intrinsic safety of the system and its possible implementation into a multi-criteria approach related to the overall safety performance of upstream operations. The aim of this novel tool is to grant the competent Authority a reliable access to drilling data for the due analysis in case of accident, also in the light of taking the necessary legal actions. Virtual Black Boxes are designed, implemented and managed in order to ensure data safety and data security, also to prevent manipulation of the records, in compliance with the requirements of Directive 2013/30/EU and its Italian transposition.

Drilling risk can be migrated based on borehole failure mechanism analysis, which provides valuable information for wellbore stability and formation damage protection. It is very challenging to identify the borehole failure in oilbase mud environment because of lacking of high resolution borehole image although we can get some information from cutting shape or sonic data with high uncertainty. A new photorealistic micro-electrical imager for oil-based mud provides rich information on borehole failure and related formation damage from 3 different images (resistivity, permittivity and stand-off). The different borehole failure mode including tensile, compressional or shear are easily identified from resistivity or permittivity image. The multiple arm radius data of this imager was also used to for borehole failure identification complementing with image feature interpretation. The special stand-off image was integrated for borehole failure identification as well. One case study from Clair field, west of Shetlands North Sea was presented to demonstrate the borehole failure identification. The horizontal incipient breakout in horizontal well provides the consistent extensional stress regime; the breakout from vertical well show the new understanding of minimum horizontal stress and the mixture of drilling induced fracture and incipient breakout indicate the small ratio of two horizontal stress. The one dimensional mechanical earth model (MEM) of a horizontal well was updated based on borehole failure mechanism. The new MEM is more consistent with field leak of testing in other wells and provide valuable information for mud optimization to improve drilling efficiency in different risk intervals. The new high-definition OBM-adapted micro-electrical imagesenabled confident identification and quantification of borehole tensile orshear failures and provides direct evidence for single well geomechanics earth model calibration.

Be it electrical signals in resistivity logs, radioactivity in gamma ray logs or magnetic moments of hydrogen protons in NMR logs, most logging techniques use an indirect approach to estimate permeability, which, in simple terms, is the measure of the ease with which a fluid of given viscosity can flow through porous media. These logging techniques are often expensive, requiring downhole equipment and, at times, other complimentary logs to obtain the permeability profile. In this paper, we propose and demonstrate a cost-effective, injection-based logging technique to obtain a continuous injectivity and permeability profile. This technique does not require any downhole equipment. Accurate flowmeters and pressure sensors at the wellhead are sufficient. An in-situ pilot test was performed in a tight overburden formation. The in-situ test data gave clear indications of permeable zones and were found to be in good agreement with the NMR derived permeability log calibrated on core data. We also present interpretation techniques to interpret the data from the injection-based log tests and obtain a continuous permeability profile of the near-well zone. This interpretation technique uses an exact solution to the unsteady flow problem, obtained using ‘Bessel-Fourier’ series. A demonstration of this log test, in a laboratory model that is representative of a multilayer formation, is presented. The test results correctly showed the presence of permeable layers and were interpreted for permeability. Permeabilities thus obtained displayed a strong correlation to the benchmark permeability values of the samples.

The development of basement reservoirs can add significant upside to regional reserves but because of perceived drilling complexity are often overlooked or underexplored. Modern drilling technologies, such as directional drilling and formation evaluation while drilling, have been shown to improve commercial viability of appraisal and development projects in frontier areas. A granitic Type-1 fractured basement reservoir offshore West of Shetland was horizontally drilled and evaluated by means of directional drilling (DD) and logging-while-drilling (LWD) technologies. This was the first time that drilling and completion of a 1-km horizontal basement well had been attempted in the UK, and the project goals were successfully achieved. The project as planned fell into the extended-reach drilling (ERD) envelope, defined as a well in which the ratio of measured depth (MD) is greater than two times the vertical depth. The ERD ratio [MD to true vertical depth (TVD)] was 2.21. This success resulted from a combination of drill bit selection, bottomhole assembly (BHA) stabilisation optimisation, rotary steerable drilling system usage, and close cooperation between the operating company and service providers. The logging data acquired were of sufficient quality to support detailed petrophysical study. The basement reservoir section was shown to have significant storage capacity within a network of fault zones, joints and microfractures, as identified using a LWD resistivity microimaging tool. The LWD imaging data were compared to offset well wireline imaging data and used to evaluate the microfracture and joint network across the horizontal section. This evaluation confirmed the storage capacity of the reservoir and was later supported by successful commercial extended well testing. In addition to fracture characterisation, the LWD data were successfully used to evaluate the fracture porosity. Fracture porosity and fracture characteristics in the horizontal well were both consistent with those derived from previously drilled inclined wells, providing the operator with confidence in its reservoir model. This paper documents the drilling and petrophysical evaluation of the first 1-km horizontal well in a fractured basement reservoir on the UK continental shelf. Further development of similar hydrocarbon-bearing basement fields would greatly increase regional recoverable reserves.

We examine the along-hole profiles of oil and water in the highly deviated drain of a light oil carbonate reservoir offshore UK, and analyse the discrepancy between the volumes calculated from LWD resistivity-porosity (Archie) and from magnetic resonance and dielectric dispersion wireline tools conveyed by open hole tractor. We also correlate the petrographic analysis of these bioclastic (ostreiid) grainstones and packstones to the logs responses and rock types. Following the acquisition of LWD resistivity and porosity logs, additional formation evaluation logs – a combined tool string of NMR, dielectric dispersion, borehole images and formation pressure – was recorded in a single run conveyed by an open hole tractor between the toe and heel of the highly deviated (60-70 deg.) drain. The water volume profile calculated from resistivity-porosity Archie analysis – the only data type available in earlier wells – is compared to the volumes of capillary bound water from NMR and to the dielectric dispersion water-filled porosity. In a well drilled with oil base mud, we expect that oil filtrate invades the formation, so that the water volume measured by dielectric dispersion represents capillary-bound plus clay-bound water volume and should be equal to the bound fluid volume measured by a NMR tool. Differences between these water volumes represent either formation evaluation anomalies or the presence of free (moveable) water. Guided by the petrographic analysis of core samples from the same formation and the textural information from the NMR and dielectric dispersion logs, 3 main rock types are identified, to be propagated onto the other field wells with conventional porosity, resistivity, and GR logs. The evaluation of LWD resistivity-porosity logs provides moderate and almost constant water volumes along the length of the drain, seemingly independent of total porosity variations. In contrast, the water volumes from NMR and dielectric dispersion are more variable, correlating well with total porosity and with the laminated features observed on the borehole images. We also observe that the NMR bound fluid water volume matches the dielectric water volume, and that they are both larger than the resistivity-porosity Archie water volumes. We propose that the NMR and dielectric water volumes are correct and correspond to variations in reservoir properties in the different rock types, that the more accurate hydrocarbon volume profile is provided by the difference between total porosity and NMR bound fluid volume or dielectric porosity, and that water is at irreducible saturation along the whole drain section. Although the NMR and dielectric dispersion logs have been used before to resolve carbonate formation evaluation problems, they have rarely been used in highly deviated drains and it is likely that the tractor conveyance and tools combination is unique to this project. Bioclastic (ostreiid) grainstone and packstone reservoirs are also rare, as is the correlation of petrographic analysis to NMR and dielectric dispersion logs in this environment.