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Abstract The reservoir formation in a major oilfield in South of Iraq is highly fractured. The operator has set as requirement that any losses had to be cured before drilling ahead. Whenever losses are encountered, drilling is stopped to cure the losses, most of the times spotting at least four cement plugs before drilling ahead are required. The current process leaves the well in an underbalanced condition for a long time posing well control risk. It was necessary to come up with an optimized solution that reduces this exposure. Drilling the entire reservoir formation to expose all loss zones before spotting cement plugs to cure all the losses was the first step taken. Secondly, since encountering total losses across the reservoir formation was inevitable, redesigning the cement slurry formulation was an objective. Many alternative designs were proposed but were disqualified as some of the chemicals or fibers were not bio-degradable causing some damage to the reservoir. After a consensus between all parties, it was proposed to introduce temperature-degradable fibers into the cement slurry. Pilot tests were performed at maximum anticipated downhole temperature which proved successful. The analysis results from the lab were approved and one well was assigned for the field test of the proposed solution. The selected well was drilled to expose all the loss zones, losses were encountered as expected, cement slurry incorporated with temperature degradable fibers was spotted which resulted in all the losses getting cured at the first attempt. This solution was tested in all subsequent wells drilled on the field achieving the same successful result. This solution has since been adopted for curing total losses encountered across the reservoir formation in this field as it ensures that less time is spent on curing losses, less cement material is consumed and those wells are delivered quicker and at reduced cost. This solution has led to average savings of approximately 5 days per well drilled subsequently on this field. Previously it took an average of 166 hours to restore fluid well control barrier (see wells 1 and 2 in figure 2), these days in 52 hours fluid well control barrier is fully restored barrier (see wells 3 and 4 in the attached image). Well control risk is greatly reduced. This paper will show how minor changes to operational procedure and improvement to conventional solutions can greatly impact well control and the quick restoration of well barrier element when drilling across highly fractured reservoir formation. It will also discuss the comprehensive analysis of the loss zones, the cement laboratory analysis, the trial jobs, the measures that were put in place to reduce operational risks in order to ensure that the job was executed successfully.
Abstract All wells require casing strings so that the planned operations can proceed. Ensuring a good quality casing set is vitally important. When conducting the calculations for frictional pressure losses the casing couplings are not taken into consideration. In API calculation methodologies for drill pipe the effect of tool joints is not taken into calculation. However, the small clearance between the casing coupling and the hole size is definitely creating an additional frictional pressure drop in comparison to the calculated which under normal circumstances taken into account the nominal casing outer diameter (OD). In this study the effect of casing couplings is taken into consideration when calculating the annular frictional pressure losses to drive the Equivalent Circulating Density (ECD). The generally accepted frictional pressure loss equations are used for a variety of casing running scenarios. The methodology that is introduced in this research study is a step change for automation in drilling operations. The findings are used to compare with the conditions during which the effect of casing couplings is not taken into consideration. The general findings indicate that annular frictional pressure losses are very critical for all wells but especially for the wells with narrow drilling margins. This research study reveals that annular frictional pressure losses are very critical for the successful casing running operations not only during circulations through the casing string but also at the time of the cementing of the same. The introduced methodology that takes into consideration of casing couplings can be used for automation in drilling operations.
Biyanni, Hanifan Mayo (Adnoc Offshore) | Al Ameri, Suhail Mohammed (Adnoc Offshore) | Couzigou, Erwan (Adnoc Offshore) | Gohel, Prashant (Adnoc Offshore) | De Barros, Adelson Jose Calleia (Adnoc Offshore) | Alhammadi, Yousef Ahmed (Adnoc Offshore) | Al-Marzouqi, Adel (Adnoc Offshore) | Al Ameri, Fahed Salem (Adnoc Offshore) | Hathaway, Neil (Deep Casing Tools) | Kerr, Edward (Deep Casing Tools)
Abstract The paper will describe a novel approach of deploying casing through a problematic open hole. It involves a drillable hydraulic motorized casing reamer shoe that can rotate freely without aid of pumping, but once resistance is encountered, pump pressure can then be applied to engage the drive mechanism inside the tool. Thus it will turn into a high-speed reaming shoe that delivers sufficient reaming action. A market research was done to find a quick intermediate solution to tackle difficulty in deploying casing down to section TD. A turbine based motorized reamer shoe was then selected to encounter the challenge with some risk mitigation in place. The first deployment was run in the well where it was identified as a challenging well context and had experienced casing being held up in the first run. Despite the fact that a wiper trip has smoothened the hole condition, the parameters that were captured during the running, the finger printing, the cementing job, and the drilling out of the shoe had ticked some boxes to evaluate the suitability of the technology implementation in the field. Moreover, the lessons learned from the first run itself has also led to further testing and modification of the tool design/setup itself. The detailed analysis and operation feedback from casing running job and subsequent operation will be beneficial to provide other operators in assessing the minimum requirement and suitability of this technology utilization to overcome the drilling challenge.
Iraq's state-owned Basra Oil Co. (BOC) may end up buying ExxonMobil's operator stake in the giant West Qurna-1 oil field, after Chevron declined the offer and Iraq briefly considered options that included purchases by its Chinese partners. Oil Minister Ihsan Abdul Jabbar told a news conference on 3 May that his ministry is discussing BOC "taking ownership of the Exxon stake in West Qurna-1 and leading the project, as happened with Majnoon," Reuters reported. Like West Qurna-1, Majnoon is in southern Iraq near the Iranian border and is considered one of the world's largest untapped oil reserves. BOC took over the field when Shell and Petronas exited in 2017 citing declining profitability as oil prices fell. As part of a global debt-reduction strategy, ExxonMobil had submitted a request in January to sell its 32.7% stake in the West Qurna-1 field.
Iraq may turn to China to meet its deadline of finalizing the sale of ExxonMobil's 32.7% stake in the West Qurna-1 oil field by the end of June, after Chevron declined to buy out its rival's position. Earlier this month, Iraq's oil ministry had signaled it preferred a US company to replace ExxonMobil as operator of the field near Basra. But when Chevron declined the offer, state-run Basra Oil Co. (BOC) widened its net to consider buyers from outside of the US, BOC Director General Khalid Hamza told Reuters in an interview. "We have no objection either on PetroChina nor CNOOC, they are our partners already," Hamza told Reuters, adding that also "BOC may buy Exxon's share, or any of the oil ministry's companies may buy." ExxonMobil submitted a request in January to sell its stake in West Qurna-1 so as to shed some of the more than $70 billion in debt it accumulated in 2020; debt that resulted in two downgrades by Moody's Investors Service in less than a year, according to Reuters.
Alkinani, Husam (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology)
Abstract One of the most vital reservoir properties is permeability. It is usually measured using core samples with two major measurement methods; using gas or using liquid. The purpose of this work is to use a data-driven recurrent neural network model to estimate the equivalent liquid permeability based on gas permeability. By using this model, the equivalent liquid permeability can be predicted for the permeability of core samples with rich clay minerals measured using gas (or any core sample that is measured using gas). This will give an alternative way to the currently used method (Klinkenberg method). Core sample data measurements of more than 500 cores were obtained from limestone formations. The data went through a processing step to eliminate any measurement errors. Then, the data were clustered into training, validation, and testing. After many iterations, a decision was made to have a network with four hidden layer and twenty neurons in each hidden layer, and four delays in the input and the output. The findings showed that the network had stopped training after nine epochs with a validation mean squared error (MSE) of 5.3. The model exhibited excellent performance during training, validation, and testing with an overall R2 of 0.91 which is excellent. These findings prove that the model can closely track the actual equivalent liquid permeability measurements using the gas permeability measurements data within a reasonable margin of error. With the rise of machine learning and other artificial intelligence (AI) methods as well as the potential application in the petroleum industry, these methodologies can revolutionize the industry and save time and money.
Alkinani, Husam Hasan (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb Tuama (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology)
Abstract Lost circulation and problems related to drilling present a major challenge for the drilling industry. Each year, billions are spent to treat these problems. There is not a single solution to lost circulation because of the complexity and kind of formations susceptible to this issue. Lost circulation treatment data for the Shuaiba formation (induced fractured formation) were gathered from drilled wells in Southern Iraq (over 2000). Treatments have been grouped according to the volume of mud loss as complete, severe, and partial loss remedies. Detailed costs and probabilities calculations were conducted. The costs of three types of loss treatments (partial, severe, and complete) were handled separately since some treatments of severe, and all treatments of complete losses have to be introducing through open end drill pipe (OEDP). Expected monetary value (EMV) and decision tree analysis (DTA) were utilized to choose the optimal mud loss pathway to treat the lost circulation type. In this study, probability and cost were both considered to select the practical and efficient strategy of stopping mud loss. Too many of the remedy scenarios were investigated. The selection of the optimum strategy for every type of loss was based on the lowest EMV and efficiency. Once both conditions were satisfied, the treatment strategies were selected to treat each type of loss. Treatment strategies were provided for complete, severe, and partial losses as flowcharts that can be utilized as a reference in the field to stop or at least mitigate this troublesome problem. The methods used in this paper have the possibility to be adopted and invested to treat mud loss based on historical data of treatments in any formation worldwide.
The Rumaila Field is in southeast Iraq and contains multiple reservoir intervals, including the Upper Cretaceous Mishrif carbonate reservoir, one of the major reservoirs in the world, that has been producing for more than 50 years. One of the key challenges in the Mishrif is to characterize the pore-structure distinction between primary and secondary porosity. The secondary porosity in the form of large pores, if present, dominates the petrophysical properties, especially permeability. Advanced logs, e.g., nuclear magnetic resonance (NMR) and image logs, can be used to understand the variations in pore structure, both qualitatively and quantitatively. In this paper, we focused primarily on four new wells with very comprehensive logging and coring programs. NMR logs were acquired using different tools and pulse sequences. This resulted in uncertainty in porosity and T2 distributions and, consequently, complications in the NMR interpretation. We observed two key issues: porosity deficit due to lack of polarization and T2 distribution truncation due to the low number of echoes. We used a single pore model to reproduce the NMR response in different pore sizes and fluid types for different pulse sequences. The results showed that the NMR response, especially in water-filled (water-based-mud filtrate) large pores, is sensitive to polarization time, echo spacing, and tool gradient strength. NMR log data confirmed the modeling results. We recommended an optimum pulse sequence and tool characteristics to fully capture the heterogeneous rock and fluid system in this carbonate reservoir. NMR logs, when available, were the primary tools to identify the large pores. We present a consistent workflow for NMR log analysis that was developed to identify and quantify large pores and extended to all wells in the field. We used advanced NMR interpretation techniques, e.g., factor analysis (NMR FA) (Jain et al., 2013), in a series of oil wells drilled with water-based mud. Using factor analysis, we identified a cutoff value of 847 ms for large pore volumes. In this manuscript, we also present an integration of laboratory measurements, e.g., NMR, mercury intrusion capillary pressure (MICP) data, whole-core CT scanning, and thin-section analysis, in our interpretation workflow. We also compared the large pore volume from image logs with NMR logs and other laboratory data and observed very consistent results. All the available information was integrated to build an “NMR-based” petrophysical model for porosity, rock type, permeability, and saturation determination. The NMR-based model was very comparable with the classic flow zone indicator (FZI) rock typing. The results of this study were used to modify the NMR acquisition program in the field and to build a petrophysical model based on only NMR and image log measurements for carbonate reservoirs. In this paper, we will discuss NMR modeling and corresponding log data from various wells to confirm the results. Furthermore, we will present a novel interpretation workflow integrating laboratory measurements and log data, which led to the modification of the NMR acquisition program in the field and the creation of a data-driven petrophysical model based on only NMR and image log measurements for carbonate reservoirs.
Schlumberger has won a $480-million deal to drill 96 oil wells in southern Iraq for the country's Basra Oil Company (BOC) and for ExxonMobil. The Iraqi cabinet agreed on 23 March to award the contract to Schlumberger, which has worked at West Qurna-1 field where ExxonMobil Iraq Ltd.is lead operator, according to press statements. In announcing the award, Iraqi authorities did not identify where the new drilling will take place. Schlumberger has had considerable experience in southern Iraq. ExxonMobil had awarded Schlumberger a 42-month integrated drilling services contract in 2018 to drill 30 wells at West Qurna-1; in 2010 Schlumberger had been similarly tapped to drill 10 wells in the same area.
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 200577, “Applications of Artificial Neural Networks for Seismic Facies Classification: A Case Study From the Mid-Cretaceous Reservoir in a Supergiant Oil Field,” by Ali Al-Ali, Karl Stephen, SPE, and Asghar Shams, Heriot-Watt University, prepared for the 2020 SPE Europec featured at the 82nd EAGE Conference and Exhibition, originally scheduled to be held in Amsterdam, 1-3 December. The paper has not been peer reviewed. Facies classification using data from sources such as wells and outcrops cannot capture all reservoir characterization in the interwell region. Therefore, as an alternative approach, seismic facies classification schemes are applied to reduce the uncertainties in the reservoir model. In this study, a machine-learning neural network was introduced to predict the lithology required for building a full-field Earth model for carbonate reservoirs in southern Iraq. The work and the methodology provide a significant improvement in facies classification and reveal the capability of a probabilistic neural network technique. Introduction The use of machine learning in seismic facies classification has increased gradually during the past decade in the interpretation of 3D and 4D seismic volumes and reservoir characterization work flows. The complete paper provides a literature review regarding this topic. Previously, seismic reservoir characterization has revealed the heterogeneity of the Mishrif reservoir and its distribution in terms of the pore system and the structural model. However, the main objective of this work is to classify and predict the heterogeneous facies of the carbonate Mishrif reservoir in a giant oil field using a multilayer feed-forward network (MLFN) and a probabilistic neural network (PNN) in nonlinear facies classification techniques. A related objective was to find any domain-specific causal relationships among input and output variables. These two methods have been applied to classify and predict the presence of different facies in Mishrif reservoir rock types. Case Study Reservoir and Data Set Description. The West Qurna field is a giant, multibillion-barrel oil field in the southern Mesopotamian Basin with multiple carbonate and clastic reservoirs. The overall structure of the field is a north/south trending anticline steep on the western flank and gentle on the eastern flank. Many producing reservoirs developed in this oil field; however, the Mid- Cretaceous Mishrif reservoir is the main producing reservoir. The reservoir consists of thick carbonate strata (roughly 250 m) deposited on a shallow water platform adjacent to more-distal, deeper-water nonreservoir carbonate facies developing into three stratigraphic sequence units in the second order. Mishrif facies are characterized by a porosity greater than 20% and large permeability contrast from grainstones to microporosity (10-1000 md). The first full-field 3D seismic data set was achieved over 500 km during 2012 and 2013 in order to plan the development of all field reservoirs. A de-tailed description of the reservoir has been determined from well logs and core and seismic data. This study is mainly based on facies log (22 wells) and high-resolution 3D seismic volume to generate seismic attributes as the input data for the training of the neural network model. The model is used to evaluate lithofacies in wells without core data but with appropriate facies logs. Also, testing was carried out in parallel with the core data to verify the results of facies classification.