From its beginnings in 1897 to its pinnacle as an industry whose sites are visible from outer space, offshore drilling has pioneered technologies, given rise to the tallest structures on Earth, transformed the seabed of the Earth's continental shelves into a manageable fossil-fuel resource, and provided work for millions of people. Despite innumerable obstacles, offshore drilling has successfully evolved and prospered over the last century into its most challenging environment yet--deepwater and ultradeepwater drilling. In an interview, Malcolm Webb, chief executive officer of Oil and Gas UK, stated there is "no agreed industry definition of what constitutes deep water. When we started in the North Sea 30 to 40 years ago, depths of 100 to 700 ft would have been regarded as deep water; and, as our abilities and technologies have moved forward, so the definition of what is deep has moved with it. Depths west of Shetland in the UK vary from approximately 500 ft to 6,000 ft plus."
ABSTRACT: Wellbore collapse as a result of severe borehole breakouts represents a major problem in many cases. In order to quantify the risk associated to wellbore collapse a reliable estimate of the collapse volume is necessary. In this study, a novel approach determining the depth/area/volume of collapse failure by using image processing approach is presented. Since image processing can be applied to any result set, the proposed approach is independent of any failure criterion (such as Mohr Coulomb, Mogi-Coulomb and Modified Lade criteria) and very versatile. For hydrocarbon fields where Mechanical Earth Modeling (MEM) approaches capable of predicting the spatial distribution of horizontal stresses exist, the presented image processing approach is utilized to generate an automated log of collapse volume while drilling. Based on this log, mud pressure adjustments can be undertaken while drilling a new well based on collapse volume. The main contribution of this work is the estimation of a real-time collapse volume log while drilling. It can help the drilling engineers in evaluating the mud weight effect on the hole cleaning efficiency to avoid stuck pipe problems. In addition, knowledge of the collapse volume provides better estimates on the required mud and cement volumes.
The obvious goal for drilling operators is to drill economical, safe, and stable wells by reducing non-productive time (NPT) due to wellbore stability problems such as borehole collapse and associated stuck pipe, and borehole breakdown and associated loss of circulation. A key issue for successful drilling operations in geomechanically challenging zones is considering all relevant factors including-formation strength properties, in-situ stresses, pore pressure, and applied pressure by the drilling mud. If collected, these data sets of rock strength and stress can be used to generate a Mechanical Earth Model (MEM; e.g., Abbas et al., 2018; Goodman and Connolly, 2007; Kristiansen, 2007; Gholami et al., 2014). Once the MEM is validated, it can be used to predict applications such as wellbore stability (Cheatham, 1984; Kaushik et al., 2016; Alkamil et al., 2017).
ABSTRACT: The wellbore instability problems can rise significantly if the downhole pressure is fluctuated during the tripping operation due to surge and swab effects. Even though the borehole pressure was estimated accurately by geomechanical model, the inappropriate tripping variables could reduce the proposed pressure to hold back mechanically the wellbore wall. Therefore, it is essential to include a safety factor or trip margin to account for the surge and swab pressure in the well construction stage. In this work, Numerous of wellbore instabilities in term of pipe sticking were investigated in a field in southern Iraq that revealed the drilling events experienced while pulling the string out of the hole. Thus, the swabbing effect on the bottom hole pressure was considered depend on the drilling observations and empirical equations. Swapping parameters from twenty-two wells in southern Iraq were implemented to investigate the influence of drilling practices, tools, and rheological properties on the borehole pressure variation. The combination of the drilling fluid density, yield point, plastic viscosity, BHA size, slip to slip time, tripping speed and the depth of investigations was used as input data. The mathematical formulas that account for most sensitive tripping factors were utilized in this research to consider the swabbing effects during the tripping. Afterward, commercial software was used to construct a statically derived swabbing model based on tripping data from offset wells to predict the drilling fluid reduction for particular tripping variables. The software was fed with Mud weight MWT, Flow rate FL, Weight on bit WOB, Total flow Area TFA and Revolution Per Minute RPM to get the drilling density reduction by swabbing effect based on standard linear least square method. Then, suggested tripping variables and the geomechanical model densities were plugs in the swabbing empirical model to mitigate this effect. The swapping data showed the drilling fluid density by swabbing was propositionally increased with the static fluid density and slip to slip time (TT), but the swabbing density is negatively affected by the plastic viscosity, flow rate, and the drill collar outside diameters. However, The yield point does not change the swabbing effect much. The recommended tripping variables were proposed to ensure best drilling practice and problems mitigation for the proposed mud density in the upcoming well. Therefore, tripping margin was also suggested to prevent the wellbore collapse while tripping operation in southern Iraq fields.
The downhole pressure is fluctuated during the tripping operation due to surge and swab effects. These phenomena can result in different wellbore instability issues such as drilling fluid losses or pipe sticking (Mitchell, 1988). Physically, the surge pressure can be defined as the increment in bottom hole pressure due to the drill tools (casing, drill pipe) being lowered into the well. The drilling fluid is displaced out of the hole during tripping in the hole operation leading to increase in fluid annular velocity and consequently the friction pressure loss. Contrarily, the swab pressure is described as the reduction in the bottom hole pressure because the drilling tools are pulled out of the hole (Bourgoyne, 1986). As the drilling tool tripping out of the hole, the drilling fluid flows inside the hole to replace the occupied volume by steel being pulled leading to reduction in the fluid annular velocity subsequently the friction pressure loss. These increment and reduction are related to friction pressure losses alterations by pipe movement. Therefore, it is essential to include a safety factor or trip margin to account for the surge and swab pressure in the well construction stage. Different factors contribute in tripping related pressure alterations, such as tripping velocities, drilling fluid properties, drill string eccentricities, wellbore geometry variations, and types of flow regimes (Mitchell, 1988; Srivastav et al., 2012). The high tripping speed induces an increase in surge and swab pressure while low tripping speed leads to no-productive time escalation. The viscosity and destiny of drilling fluid have a significant impact on the severity of the surge and swab pressure. The lower the clearance between the hole and drilling tool the higher the surge and swab pressures. The drill string and the types of the flow regimes are out of paper scope. Numerous mathematical model has been innovated base on different disciplines to consider the drilling fluid density alterations by the tripping operation. In this work, the drilling fluid reduction by swabbing effect have considered mitigating the mechanical wellbore instability in a field in southern Iraq. Figure 1 shows drilling time breakdown for several wells in southern Iraq, and it can be observed the tripping operation worth 30% of the total drilling time. Therefore, the tripping operation should be optimized to minimize the tripping-related wellbore failure as well as the tripping non-productive time in the shale interval specifically in the production section.
Saberhosseini, Seyed Erfan (Islamic Azad University) | Mohammadrezaei, Hossein (Iranian Offshore Oil Company) | Saeidi, Omid (Iranian Offshore Oil Company) | Shafie Zadeh, Nadia (Natural Resources Canada) | Senobar, Ali (Iranian Offshore Oil Company)
Pre-analysis of the geometry of a hydraulically induced fracture, including fracture width, length, and height, plays a crucial role in a successful hydraulic-fracturing (HF) operation. Besides the geometry of the fracture, the injection rate should be optimal for obtaining desired results such as maintaining sufficient aperture for proppant placement, avoiding screenouts or proppant bridging, and also preventing caprock-integrity failure as a result of an extensively uncontrolled fracture in reservoirs. A sophisticated numerical model derived from the cohesive-elements method has been developed and validated using field data to obtain an insight on the optimal fracture geometry and injection rate that can lead to a safe and efficient operation. The HF operation has been conducted in an oil field in the Persian Gulf with the aim of enhanced oil recovery (EOR) from a limestone reservoir with low matrix permeability in a horizontal wellbore. The concept of the cohesive-elements method with pore pressure as an additional degree of freedom has been applied to a 3D fully coupled HF model to estimate fracture geometry, specifically fracture height as a function of the optimal injection rate in a reservoir porous medium. It was observed that by increasing injection rate, all the fracture-geometry parameters steeply increased, but the fracture height must be controlled to be in the reservoir domain and not surpass the caprock and sublayer. For the reservoir under study with the maximum height of 100 m, length of 250 m, width of 100 m, permeability of 2 md, and porosity of 10%, the optimal fracture height is 73.4 m; the average fracture width and half-length are 12.8mm and 55.4 m, respectively. Therefore, the optimal injection rate derived from the fracture height and geometry is in this case 4.5 bbl/min. The computed fracture pressure (49.55 MPa = 7,283.85 psi) has been compared with the field fracture pressure (51.02 MPa = 7,500 psi), and the error obtained for these two values is 2.88%, which showed a very good agreement.
Modeling accurate lithofacies and petrophysical properties is a crucial step in the reservoir characterization as it affects reservoir heterogeneity, fluid flow modeling, and history matching, especially in complex geological structures. In this paper, the multiple-point facies geostatistics (MPFG) and sequential gaussian simulation were integrated as an efficient workflow for lithofacies and petrophysical property modeling of a fluvial sand-rich depositional environment of Zubair formation in South Rumaila oil field, Southern Iraq. The lithofacies features of the upper sandstone member has three main lithotypes derived from the core data analysis of 20 wells: sand, shaly sand, and shale.
In the MPFG, the surface map of the fluvial depositional system of the upper sandstone reservoir in Zubair formation was created through a 2D user-defined training image. The training image body and channels were pointed to the three aforementioned lithofacies as an alternative to the variogram to create the 3D facies system. Then, the surface map was sampled and trained by neural networks to create the discrete template of 3D facies distribution pattern into the 3D grid construction. The resulted pattern represents a numerical geomodel that captures all the features of the fluvial depositional environment of the reservoir, which then was adopted for 3D lithofacies modeling.
The resulting MPFG-lithofacies model reflected a more reasonable facies architecture than the sequential indicator simulation by preserving the fluvial features of the geosystem. Many realizations were generated and cross-validated to determine the most appropriate lithofacies model, which was considered later for the permeability and porosity modeling by the sequential gaussian simulation. To attain history matching, the resulting MPFG and petrophysical model was upscaled and incorporated into the compositional reservoir flow simulation for history matching. A near-perfect and fast history matching with the least mismatch was obtained with respect to observed and calculated cumulative and rates of oil production and water injection for the entire field in addition to all producers and injectors within the whole production history. The results reflect how is efficient considering multiple-point statistics to reconstruct the complex geological features to capture reservoir heterogeneity and achieve fast history matching.
Carbon Dioxide (CO2) injection is a viable technique with huge potential if employed efficiently in naturally fractured reservoirs. However, extensive computational resources are needed to evaluate and consider candidates for continuous CO2 injection projects. In this study, a new workflow is developed that captures universal fluid compositions and relative permeability data for fields undergoing continuous CO2 injection in naturally fractured reservoirs.
Injection design schemes and parameters for continuous CO2 for hypothetical reservoir types are constructed using a miscible, dual porosity, compositional reservoir simulation model. An algorithm is developed to capture varying fluid compositions and relative permeability data for the data set used in this study. Data collected from reservoir simulation cases are used to construct two Artificial Neural Network (ANN) based proxy models. Namely, a proxy for performance prediction that utilizes specific injection design parameters to predict reservoir performance and an inverse proxy for injection design that provides injection design scheme for a desired reservoir performance.
The constructed ANN's predictability is assessed through its capability of predicting blind test data within a specified tolerance. The proxy based models were capable of predicting, within an acceptable degree of error, the oil and gas production profiles as well as injection design parameters of well spacing, CO2 injection rate, and CO2 injection duration of a field undergoing continuous CO2 injection. The constructed networks were tested with real data from Twofreds field in Texas that has been undergoing continuous CO2 injection since 1974. The constructed proxy based models were able to overcome limitations imposed by the complexity of handling different compositional reservoir fluids and relative permeability data. The new methodology sets a new benchmark for universal proxy modeling as it incorporates composition based reservoir fluid and relative permeability data.
The approach presented overcome existing limitations in handling compositional reservoir fluid variations as well as relative permeability in universal workflows.
Enhanced oil recovery (EOR) techniques have gained industry focus over the past decade. EOR methods differ per application and reservoir properties requiring extensive evaluation prior to field testing. The introduction and coupling of artificial intelligence workflows enabled the utilization of intelligent systems and contributed majorly to decision making. Complex EOR applications that requires extensive time and computational power are used to configure networks that provide answers swiftly.
Alkamil, Ethar H. K. (Missouri University of Science and Technology) | Abbood, Husam R. (Basrah Oil Company) | Flori, Ralph E. (Missouri University of Science and Technology) | Medley, George (Signa Engineering Corp) | Nauduri, Sagar (Signa Engineering Corp) | Alsaba, Mortadha (Australian College of Kuwait)
Differences between mud pressure in a wellbore and pore pressure in high permeability rocks can lead to differential sticking, particularly when drilling deviated wells and encountering mud losses. Several solutions, all challenging, can be used to address this problem, where the conventional mitigation method of managing the mud weight (MW) is often used. However, managed pressure drilling (MPD) offers a promising solution with a positive risk-adjusted cost and other benefits.
Wells in the E oilfield in southern Iraq are typically drilled overbalanced and therefore often experience a high percentage of non-productive time (NPT) due to differential sticking. This study evaluates the feasibility of using MPD to optimize the drilling process by decreasing the mud weight while applying the required surface pressure to achieve the target bottom hole pressure (BHP). A simulation software, which uses different mud weights to determine the required choke surface backpressure (SBP) to achieve the targeted equivalent circulation density (ECD).
Historically, differential sticking has not been a primary driver to justify MPD. However, MPD offers more dynamic and rapid wellbore pressure control by adjusting SBP applied to the annulus for a given MW, and can actually decrease the risk of differential sticking. Instead of shifting MW or changing other drilling parameters, MPD adjusts the required ECD and/or equivalent static density (ESD) based on the formation pore pressure gradient. Additionally, MPD directly lowers SBP in the event of mud losses due to high ECD/ESD to decrease the BHP without the need to reduce MW.
This paper discusses the application of using a hydraulic simulation software to model the drilling development plan. The software optimizes MW and SBP while drilling, making pipe connections, and completing the well. Furthermore, it discusses the sensitivity effects of each parameter on wellbore pressure and provides guidelines for managing pressure by adjusting these variables.
The E onshore oilfield is located in southern Iraq and is considered as one of the largest oil and gas fields in the Middle East, with more than thirteen carbonate and sandstone reservoirs. The two main reservoirs are the Mishrif formation and the Zubair formation, with different equivalent pore pressures of 4.165 ppg and 9.5 ppg, respectively. The operator planned to drill both formations in the same hole (8 ½-in. section) to reduce drilling costs. However, this plan led to a high percentage of non- productive time (NPT) due to wellbore instability. NPT is associated with kicks, wellbore breathing, lost mud, lost circulation materials, additional casing string, stuck pipe, unplanned sidetracks, and in some cases not reaching total depth (TD) (Gravdal et al., 2010; Sugden et al., 2014).
Determining the most influential parameters affecting the reservoir flow responses is a vital step in the integrated reservoir studies for evaluation and analyses. More specifically, removing the non-influencing parameters leads to reach the optimal process design. The conventional procedure to determine the most sensitive parameters combines regression analysis with analysis of variance. However, that approach produces one reduced regression model after eliminating the non-influential parameters (deterministic approach). In this paper, Bayesian Model Averaging (BMA) was applied to stochastically identify the geological parameters that control the immiscible CO2-assisted gravity drainage process performance in a multilayer heterogeneous sandstone oil reservoir in South Rumaila oil field. After achieving acceptable history matching within approximately 57 year of production, the CO2-assisted gravity drainage injection was evaluated in 10 year future prediction. In that process, vertical wells were placed at the top of the reservoir for CO2 injection to formulate a gas cap that make oil drains down towards the bottom of reservoir. Above the oil-water contact, a series of horizontal production wells were installed to produce oil. The main geological parameters that controls the immiscible CO2 flooding are horizontal permeability, anisotropy ratio (Kv
The Gas and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been developed to overcome of the limitations of Gas flooding processes in reservoir with strong aquifers. These limitations include high levels of water cut and high tendency of water coning. The GDWS-AGD process minimizes the water cut in oil production wells, improve gas injectivity, and further enhance the recovery of bypassed oil, especially in reservoirs with strong water coning tendencies.
The GDWS-AGD process conceptually states installing two 7 inch production casings bi-laterally and completing by two 2-3/8 inch horizontal tubings: oil producer above the oil-water contact (OWC) and one underneath OWC for water sink drainage. The two completions are hydraulically isolated by a packer inside the casing. The water sink completion is produced with a submersible pump that prevents the water from breaking through the oil column and getting into the horizontal oil-producing perforations.
The GDWS-AGD process was evaluated to enhance oil recovery in the heterogeneous upper sandstone pay in South Rumaila Oil field, which has an infinite active aquifer with a huge edge water drive. A compositional reservoir flow model was adopted for the CO2 flooding simulation and optimization of the GDWS-AGD process. Design of Experiments (DoE) and proxy metamodeling were integrated to determine the optimal operational decision parameters that affect the GDWS-AGD process performance: maximum injection rate and pressure in injection wells, maximum oil rate and minimum bottom hole pressure in production wells, and maximum water rates and minimum bottom hole pressure in the water sink wells. More specifically, Latin hypercube sampling and radial basis neural networks were used for the optimization of the GDWS-AGD process performance and to build the proxy model, respectively.
In the GDWS-AGD process results, the water cut and coning tendency were significantly reduced along with the reservoir pressure. That resulted to improve gas injectivity and increase oil recovery. Further improvement in oil recovery was achieved by the DoE optimization after determining the optimal set of operational decision factors that constrains the oil and water production with gas injection. The advantage of GDWS-AGD process comes from its potential feasibility to enhance oil recovery while reducing water coning, water cut, and improving gas injectivity. That gives another privilege for the GDWSAGD process to reach significant improvement in oil recovery in comparison to other gas injection processes, such as the Gas-Assisted Gravity Drainage (GAGD) process, particularly in reservoirs with strong water aquifers.
Al-Mudhafar, Watheq J. (Louisiana State University) | Al-Tameemi, Abdullah (Louisiana State University) | Al-Maliki, Ali K. (Basra Oil Company) | Al-Attar, Atheer (Weatherford International) | Al-Ameri, Riyam H. (Basra Oil Company)
The Gas-Assisted Gravity Drainage (GAGD) process has been suggested to improve oil recovery in both secondary and tertiary recovery through immiscible and miscible injection modes. In contrast of Continuous Gas Injection (CGI) and Water-Alternative Gas (WAG), the GAGD process takes advantage of the natural segregation of reservoir fluids to provide gravity-stable oil displacement and improve oil recovery. In the GAGD process, the gas is injected through vertical wells to formulate a gas cap to allow oil and water drain down to the horizontal producer (s). The GAGD process has been invented based on experimental work at Louisiana State University. Limited studies have been conducted to test its effectiveness in real oil field evaluations.
In this paper, a comprehensive literature review was presented to summarize all the references about the GAGD process concepts, principles, and field-scale evaluations. Particularly, the paper presents introduction about the mechanisms of cO2-rock-fluid interactions, gas injection approaches for Enhanced Oil recovery, the physical model description and evaluation of the GAGD process physical Model, the factors influencing the GAGD process, and finally a review of all the previous field-scale evaluation studies. Moreover, the validation of the GAGD process in field-scale application was fully discussed by focusing the light on its weak points with respect to the optimal implementation design for achieving maximum oil recovery.
The paper ended with field-scale compositional simulations of the GAGD process in the 5th SPE comparative solution project model and the heterogeneous upper sandstone oil reservoir in the South Rumaila oil field, located in Southern Iraq. Four gas mixtures were injected: CO2, Flue Gas, Nitrogen to Methane, and associated gas production (AGP). It can be concluded that the immiscible flooding of the AGP-AGD in the South Rumaila field has the same effect of using the CO2 with respect to attaining a promising oil recovery. Consequently, AGP can be efficiently utilized for an EOR project in the Rumaila field as an alternative to the carbon dioxide.