The SPE London young professionals (YPs) group organized its very first international field trip for members in September 2009. The 2-day event consisted of 1 day of technical training, provided by Schlumberger; an evening professional networking event with Paris YPs; and 1 day of social activities in the center of Paris. The London Section sponsored travel for two students from London-based universities, as well as a representative from the Paris School of Mines. The technical training session was organized at Schlumberger's Clamart Research, Technology, and Product Center in Paris and was provided by Schlumberger, free of charge to the YP groups. During the session, YPs were given presentations on well testing, well-test design, cementing, logging-while-drilling, and production-logging technologies commercialized by Schlumberger in the field.
Bigoni, Francesco (Eni S.p.A) | Pirrone, Marco (Eni S.p.A) | Trombin, Gianluca (Eni S.p.A) | Vinci, Fabio Francesco (Eni S.p.A) | Raimondi Cominesi, Nicola (ZFOD) | Guglielmelli, Andrea (ZFOD) | Ali Hassan, Al Attwi Maher (ZFOD) | Ibrahim Uatouf, Kubbah Salma (ZFOD) | Bazzana, Michele (Eni Iraq BV) | Viviani, Enea (Eni Iraq BV)
The Mishrif Formation is one of the important carbonate reservoirs in middle, southern Iraq and throughout the Middle East. In southern Iraq, the formation provides the reservoir in oilfields such as Rumaila/West Qurna, Tuba and Zubair. The top of the Mishrif Formation is marked by a regional unconformity: a long period of emersion in Turonian (ab. 4.4 My) regionally occurred boosted by a warm humid climate, associated to heavy rainfall. In Zubair Field, within the Upper interval of Mishrif Formation, there are numerous evidences of karst features responsible of important permeability enhancements in low porosity intervals that are critical for production optimization and reservoir management purposes.
In the first phase, the integration of Multi-rate Production logging and Well Test analysis was very useful to evaluate the permeability values and to highlight the enhanced permeability (largely higher than expected Matrix permeability) intervals related to karst features; Image log analysis, on the same wells, allowed to find out a relationship between karst features and vug densities, making possible to extend the karst features identification also in wells lacking of well test and Production logging information. This approach has allowed to obtain a Karst/No Karst Supervised dataset for about 60 wells.
In the second phase different seismic and geological attributes have been considered in order to investigate possible correlations with karst features. In fact there are some parameters that show somehow a correlation with Karst and/or NoKarst wells: the Spectral Decomposition (specially 10 and 40 Hz volumes), the detection of sink-holes at top Mishrif on the Continuity Cube and its related distance, the sub-seismic Lineaments (obtained from Curvature analysis and subordinately from Continuity), distance from Top Mishrif. In the light of these results, the most meaningful parameters have been used as input data for a Neural Net Process ("Supervised Neural Network") utilizing the Supervised dataset both as a Trained dataset (70%) and as a Verification dataset (30%). A probability 3D Volume of Karst features was finally obtained; the comparison with verification dataset points out an error range around 0.2 that is to say that the rate of success of the probability Volume is about 80%.
The final outcomes of the workflow are karst probability maps that are extremely useful to guide new wells location and trajectory. Actually, two proof of concept case histories have demonstrated the reliability of this approach. The newly drilled wells, with optimized paths according to these prediction-maps, have intercepted the desired karst intervals as per the subsequent image log interpretation, which results have been very valuable in the proper perforation strategy including low porous intervals but characterized by high vuggy density (Karst features). Based on these promising results the ongoing drilling campaign has been optimized accordingly.
Reservoir simulations constitute a cornerstone to predict the flow of fluids through porous media. Various numerical models called simulators are developed to simulate the performance of hydrocarbon reservoirs. These models are used in field development since production forecasts are necessary to make investment decisions. Nowadays, numerical simulators are widely used by reservoir engineers.
In recent times, machine learning applications have garnered the interest of the oil and gas industry due their unorthodox approach to creating complex models. The more historical data that can be provided in the training phase of the computation, the more accurate the predictions utilizing less time and computational power required by the alternative. The alternative, reservoir simulation applications, require more robust hardware for processing large amounts of data in sophisticated ways. This will require several iterations and may require long computation to validate the model. Running time for a simulation is dependent on software, which can be dependent on hardware. This creates a matrix of time and resources needed to complete simple to complicated simulations.
A few studies have proposed the use of the Lanczos decomposition method in reservoir simulation studies. The attractiveness of this method appears to be the avoidance of time stepping in simulation and allows the computation of reservoir pressures at any given time directly.
In this study, two new simulators were developed using Lanczos Decomposition Method (LDM) and Conventional Implicit Time-Stepping Method (ITSM). The study focuses on 2-D flow for slightly compressible fluid of constant viscosity with multiple wells. Derivation of the model equations was performed using the continuity equation for both methods through the use of MATLAB. The simulators were written using the MATLAB programming language. The simulators developed in this study are capable of assigning uniform and non-uniform gridblock distribution; porosity and permeability distributions, as well as developing various production and injection scenarios for single or multiple wells depending on different areas of application. Validity and accuracy of the 2D flow simulator were examined by comparing simulation results with that obtained from the commercial software called ECRIN. The results of the simulator were almost identical with the results obtained from the commercial software. During the model runs, the CPU time of the two simulators were compared. A special case was also studied for a single well with variable rate history using both ITSM and LDM written with FORTRAN.
To date, in petroleum engineering literature, there is no work published that compares the performances (in terms of computational aspects as well as CPU times) of the Lanczos method and the conventional implicit-time stepping method.
Raghunathan, Murali (ADNOC - Al Dhafra Petroleum Company) | Alkhatib, Mohamad (ADNOC - Al Dhafra Petroleum Company) | Al Ali, Abdulla Ali (ADNOC - Al Dhafra Petroleum Company) | Mukhtar, Muhammad (ADNOC - Al Dhafra Petroleum Company) | Doucette, Neil (ADNOC - Al Dhafra Petroleum Company)
A novel workflow was developed to select an optimal field development plan (FDP) which accounts for a number of associated uncertainties for an oil Greenfield concession that has a limited number of wells, production data and information. The FDP was revisited and updated to address the additional data acquired during the field delineation phase. The study in Ref-1 demonstrates the comprehensive uncertainty analysis performed and the resulting optimized FDP. The FDP was developed to minimize the economic risk and uncertainty. Further field delineation activities have revealed a north and south extensions with an increase in hydrocarbon accumulation by 115%. A reservoir dynamic model was updated because of the increase in HC and input data from 17 wells. A workflow has been created with a suitable development option to consider the recently appraised areas, which are: - Updated saturation height functions (SHFs) which improve the match between newly drilled wells and water saturations logs - Updated reservoir models which were based on well tests and new analytical interpretations - History matching well test data with new acquisition data - Optimized field development options, that cover additional areas - Inputs to reservoir surveillance plan Be implementing following an extensive analysis the most robust development concept was selected and will now in the field.
The Yibal Khuff/Sudair reservoirs were discovered in 1977. The field contains both Non-Associated Gas in the Sudair & Lower Khuff reservoirs and Associated Gas with oil rims in the Upper Khuff reservoirs. The Upper and Lower Khuff hydrocarbons contain 2–3% H2S and 4–6% CO2, whereas the Sudair gas contain 1–1.5% CO2 and less than 50 ppm H2S. The Field Development Plan (FDP), a multibillion dollar sour development project, was completed in 2011 proposing a total of 47 wells, 34 dedicated horizontal/vertical wells for oil rim production and 13 commingled vertical/deviated gas wells, and the construction of new sour surface facilities with a gas production capacity of 6 MMm3/day.
FDP execution started in 2016 while the details of field start-up, scheduled a few years later, were still being planned. As part of this planning, it was noticed that a number of pre-drilled wells required perforation and clean-up before facility startup. Due to the time necessary to prepare all the pre-drilled wells, pre-production wellbore cross-flow was expected to occur in wells located in the West block of the field. A dedicated subsurface team was assigned in 2017 to evaluate and mitigate the potential risks associated with this expected cross-flow through the wellbore resulting from the pressure difference between the Lower Khuff and Upper Khuff layers.
This paper covers the integrated approach that the team followed to address the expected cross-flow issue, including: Basis for pre-production cross- flow The quantification of the cross-flow using analytical and numerical simulation methods The assessment of the impact of cross-flow on process safety and the environment (i.e. drilling risks with potential blow out of sour gas) and social responsibility (i.e. production capacity and ultimate recovery losses resulting in lower benefits to the community) The identification and assessment of solutions to stop/reduce the cross-flow The implementation of a robust and feasible mitigation plan
Basis for pre-production cross- flow
The quantification of the cross-flow using analytical and numerical simulation methods
The assessment of the impact of cross-flow on process safety and the environment (i.e. drilling risks with potential blow out of sour gas) and social responsibility (i.e. production capacity and ultimate recovery losses resulting in lower benefits to the community)
The identification and assessment of solutions to stop/reduce the cross-flow
The implementation of a robust and feasible mitigation plan
The conducted study demonstrated that the impact of cross-flow at well level would be severe. The cross-flow rate could reach up to 25-137 Km3/day/well, while the field level cross-flow rate could reach up to 400 Km3/day. The oil rate capacity reduction in the West Block wells could reach 20-30% at start-up, resulting in a total only 1% oil ultimate recovery loss at field level since the West block contribution is small to total production and West block wells are constrained. The study also showed that the casing design is adequate and drilling risks are manageable even in case of cross-flow. Out of several solutions identified to stop/reduce cross-flow, phasing perforation was considered the most robust and feasible option.
This paper presents the novel approach of a collaborative study that resulted in improved safety and reduced environmental risks and potential ultimate recovery losses. It also presents the methodologies used to allow the Assessment and Mitigation of Pre-Production Cross-flow and evaluation of the best option to mitigate the cross-flow in order to minimize the impact of cross-flow at minimum cost, well interventions and impact on well deliverable.
The method for modeling of a multilateral well design that is completely independent on the simulation grid and fluid properties is proposed. The method takes into account friction in the lateral branches and crossflow between them. Well parameters, such as trajectory, perforation intervals, roughness and diameter, are directly used to calculate pressure distribution along the wellbore at the current fluid composition and tubing head pressure (THP).
Well connections with grid blocks in a finite volume approximation for dynamic model should be created. The automatic creation of the well connections during dynamic simulation based on specified well trajectory and completion intervals is proposed. The connection factor is suggested to be calculated based on length of completion intersection with the block, trajectory direction and rock properties during the run time. To calculate pressure drop on well track intervals between connections and the well track intervals between top completion and tubing head the well-known correlations are utilized. The correlations are used for the current fluid composition in the wellbore in each connection using information for well trajectory, roughness and diameter.
Such an approach makes it possible to get rid of the use of the tabulated bottomhole pressure (BHP) as a function of tubing head pressure for a number of phase compositions. Such traditional use of phase compositions gives a non-physical response in compositional models, where the component composition of the product varies significantly throughout the life of the field. Usage of real coordinates (x, y, z) for setting well trajectory and perforation intervals, instead of the traditional grid block numbers (i, j, k), allows to calculate layer intersection, connection factors and pressure distribution along wellbore with arbitrary changes in the dynamic model grid, for example, when introducing local grid refinement or dynamic grid and rock properties variation used to describe hydraulic fracturing.
The proposed method is successfully used for modeling of a multilateral well design in dynamic simulation. The results of such dynamic simulation are consistent with the real samples from reservoir.
Data-Driven subsurface modeling technology has been proven, for the past few years, to yield technical and commercial success in several oil fields worldwide. A data-driven model is constructed for the first time for an oil field onshore Abu Dhabi, and used for evaluation of a reservoir with substantial reserves and comprehensive development plan; for the purpose of predicting production rates, dynamic reservoir pressure and water saturation, improving reservoir understanding, supporting field development optimization and identifying optimum infill well locations. The objective is to provide the asset with a decision-support tool to make better field development planning and management.
The subject reservoir is a low permeability carbonate reservoir and characterized by lateral and vertical variations in its reservoir rocks and fluid properties. More than 8 years of Phase-I development and production/injection data and extensive amount of well tests and log data (SCAL, PVT, MDT) from more than 37 wells were used to construct the Data Driven Model for this asset.
This new modeling technology, (TDM), integrates reservoir engineering analytical techniques with Artificial Intelligence, Machine Learning & Data Mining in order to formulate an empirical and spatiotemporally calibrated full field model. In this work, it is leveraged with other conventional reservoir modeling and management tools such as streamline modeling, isobaric maps and flooding conformance.
Several analyses were performed using the full field data-driven model; complementing the existing conventional numerical model. The accomplishments of the data-driven reservoir model for this project included, but not limited to, comprehensive history matching (including blind validation) and then forecast of Oil rate, GOR, WC, reservoir pressure and water saturation, injection optimization, and choke size optimization. The results generated by the data-driven model proved to be quite eye-opening for the asset management; as the model was able to identify potential areas of improving field efficiency and cost reduction.
When combined with numerical techniques, the calibrated data-driven model assist to obtain a reliable short term forecast in a shorter time and help make quick decisions on day-to-day operational optimization aspects. The use of facts (all field measurements) instead of human biases, pre-conceived notions, and gross approximations distinguishes data-driven modeling from other existing modeling technologies. Its innovative combination of Artificial Intelligence and Machine Learning (the technologies that are transforming all industries in the 21st century) with reservoir engineering, reservoir modeling and reservoir management clearly demonstrates the potentials that these pattern recognition technologies offer to the upstream oil and gas industry for its realistic digital transformation.
Several mature fields in the North Sea experience significant challenges relating to high pressures and temperatures accompanied with the infill drilling challenge of very narrow margins between pore and fracture pressures. To navigate these narrow mud weight windows, it is critical to understand the bottom hole pressure. However, in the cases of fractured formations above the target zones, severe losses can be encountered during drilling and cementing operations often leading to the inability to maintain a full mud column at all times and even threaten the ability to reach TD.
The operator therefore decided to investigate the use of a new acoustic telemetry system that could provide internal and external pressure measurements, (along with other downhole measurements) independently of traditional mud pulse telemetry in the drilling assembly. Real-time distributed pressure data essential to understanding the downhole conditions could therefore be provided regardless of circulation, even under severe losses or during tripping and cementing operations.
This acoustic telemetry network was deployed on several wells through multiple hole sizes and including losses management, liner running and cementing operations.
The initial primary purpose of running the network was the ability to monitor the top of the mud at all times, even in significant loss situations. As real-time data was acquired it became apparent that the data could also be used in real-time to aid and help quantify the actual downhole pressures. The use of this downhole data was modified and new calculations designed for simpler visualization of equivalent circulating densities at the shoe, bit and identified weak zones in the well at depths beyond the acoustic tools themselves. This data was used to manage the bottom hole pressure within a 300 psi mud weight window to ultimately enable the well to be delivered to planned TD.
The tool and calculations helped verify managed pressure connections and subsequent pump ramp up and down operations to minimize pressure fluctuations in the well. Additionally the data was used during dynamic formation integrity testing and to measure and calculate ECD at various positions along the drillstring and casing when downhole PWD measurements were unavailable.
This paper will describe how the implementation of new technology through the downhole acoustic network was deployed and the lessons learned in how the real-time data was used, changed and adapted in this particular well. Due to this deployment the acoustic telemetry network will now be used on upcoming equally challenging wells and its range of operations expanded to include drilling, tripping and liner cementing operations.
The well discussed in this paper has a history of sand production and has exhibit long cyclic slugging behavior with a frequency of several days and reduced average production. The lower completion has a 2000-ft gap between the mule shoe and the packer that is exposed to the larger diameter of 7-in. liner. It is not fully understood whether the slugging is caused by the gap at the lower completion or by sand transportation or both.
Dynamic wellbore modelling with sand particle transport is essential to model the abovementioned complex slugging behavior. A stepwise approach was adopted to allow systematic evaluation of this complex slugging phenomenon. Initially, a lumped inflow with no sand transportation was assumed. In the next stage, sand transportation was included with zonal inflow details added. Several sensitivities on sand particle sizes, particle density, zonal productivity index, etc. were carried out, all of which were aimed at reproducing the long cyclic slugging behavior observed in the field.
Transient simulations successfully produced the slugging behavior observed in the field. Cyclic slugging was seen to be caused by the flow dynamics generated by particles of small to medium size. Some of the key findings were complete blockage by porous sand stationary bed at the lower completion gap (with subsequent pressure buildup), transition from stationary bed to moving bed, rate-dependent velocity of a slow-moving particle bed (eventually producing to surface), and fresh sand particle production from the reservoir at increased drawdown. Measured data from the sand detector confirmed the production of sand, particularly around the same period as predicted by simulation.
Potential slug mitigation solutions were established that should help to achieve higher and stable production. One solution was to achieve higher flow velocity and therefore enable sand transportation as a continuous moving bed (i.e., no blockage), such as reducing the gap size at the lower completion section together with either tubing size reduction or electric submersible pump (ESP) installation. The other solution was to implement an appropriate sand control/sand consolidation method.
Sand production is a common flow assurance issue and sometimes can result in unstable flow behavior causing reduced production. This work is the first attempt to implement particle transport modelling in transient multiphase flow simulation to successfully address a slugging issue in a real well. The analysis helped in understanding the mechanism causing the slugging and arriving at a potential mitigation solution. Further, it provides a step-by-step workflow and a template to address such problems.
The North Sea Oil and Gas industry counts over 7,800 wells drilled. The industry is now entering an era of well abandonment and decommissioning. Current barrier verification for P&A requires appropriate pressure testing and includes surface and downhole monitoring.
Globally, Spectral Noise Logging (SNL) has been utilized in many thousands of cases to detect fluid movement behind completion tubulars and/or across a cement barriers.
In Nov 2017, full-scale verification tests were conducted at the International Research Institute of Stavanger (IRIS). These tests were conducted in a controlled environment to verify current technology thresholds. These showed the technique validated the cement barrier integrity during pressure tests and can diagnose channeling as low as 9 ml/min behind the casing. The threshold matrix for different cement defect versus pressure and flow rates allowed the usage of the technology to support the positive qualification of the barrier elements (
Utilizing a purpose-built test assembly of standard oilfield tubular and cement with fitted end caps, a series of pressure tests operations were conducted to identify the pressure and associate leak rates in conjunction with the SNL. The results clearly demonstrated that the logging tool can provide evidence of barrier verification over a wide range of well applications. Barrier qualification requires that three conditions are met; firstly, cement behind casing is in place and not displaying a micro-annulus or any form of fluid movement behind pipe. Secondly, that a cement plug holds pressure and there is also no fluid leak and finally natural shale barriers are active and create a sufficient barrier. Currently, technology is in its 10th generation, and since the IRIS tests have been used in many wells, covering both onshore and offshore oil and gas wells and wells in highly sensitive environmental areas. On each case the logging operations were used to verify well status before and after the barrier establishment via cement squeeze or section milling and, in several cases, clearly, demonstrate that the barrier status remained ineffective, hidden and further remedial work was required.
This paper discusses the downhole passive noise listening and its spectral analysis technique to prove the effective cement barriers are in place. The concept, methodology and its application which have been successfully tested via yard and field tests are presented in this paper.