Previously published technology that was not used in a company was implemented using a new approach based on marketing technology that resulted in widespread adoption and a lasting change. The drilling technology was available for years in SPE papers. Previous attempts to implement it failed to establish lasting application. The initiative took about two years and resulted in the use of the technology being well established. In addition to the process used to implement the initiative, the drilling technical process is also summarized.
The initiative drove implementation of the use mechanical specific energy (MSE) and other techniques to identify and minimize bit dysfunction and bit and bottomhole assembly vibrations. Full implementation of the techniques required drilling managers, superintendents, and engineers in the office, company drill site managers on rigs, and drilling contractor and service company personnel both on site and in the office all to understand the value of the technology, as well as know how to apply it.
The implementation process included an initial awareness phase of sharing successes by early adopters to create demand for the technology. Implementation included comprehensive training, management support, technical tools, and ongoing support.
The result of the initiative was a dramatic improvement in drilling performance. Significant increases in rates of penetration were achieved with virtually no added operational cost. Good results have been obtained in all business units, and the processes have evolved into routine practices.
The key conclusion is that proven marketing techniques can be adapted and applied to internal initiatives. The technology of marketing is effective and available, but adapting it to use internally is not trivial or obvious. On some previous initiatives, the approach was to deliver the technology, then create demand for it. The technique used this time was to create the demand first, then deliver the technology. This approach was successful in reducing opposition.
Early adopters must be identified and supported. Their initial successes are used to create demand for the technology and willingness to participate in training and learning. Training must be delivered to all of the people involved to enable application of the new process or technology.
Management support and technical support are both essential to get past difficulties. Patience and understanding are the best techniques to deal with resistance. Ultimately, successful results are the key to full adoption, but successful results cannot be achieved without the previous steps.
This case history includes both the principles and the application to a real case, with enough information on the drilling technology to understand the marketing process. The novel and additive information is how to adapt marketing technology for internal use, which is important for companies to adopt new technology faster.
One of the primary energy sources, natural gas is widely used for power generation, industrial production, transportation, commercial buildings, and households. The industry is a capital intensive one for all stages from exploration to delivery. Two types of supplies: pipeline and Liquefied Natural Gas (LNG), recently have faced a direct intra-industrial competition. Physical nature of methane and associated transportation costs lead to domination of so-called "natural monopolies" or "national champions" and strict government regulation, which postponed the development of free trade and competition. After decades of technical innovations and cost curve improvement in LNG sector, shale boom in the USA, increasing global consumption, and demand for supply diversification reformulated the role of gas in the global energy balance. While the pipeline sector remains to be in the hands of large corporations and a subject of strategic interstate and international agreements, or LNG provides more diversity and flexibility of trade. However, even after a long history of LNG shipment since the late 1950s, LNG market is still regional with high spreads between countries and terms of delivery.
The paper presents the evolution of business models in the natural gas industry, focusing on the primary drivers as government regulation, production technologies, and regional markets trends on the way to liberalization and cointegration. Thus, our primary objective is to show relative influence power of these drivers. This analysis also defines the competitiveness of corporate business model under conditions of asymmetric information, regional gas markets, deregulation trends, fast-growing production technologies and downstream infrastructure (specifically in LNG sector). We also enclose the analysis of the most globally competitive gas projects. We analyze changes in value chain change and trading contracts. Our methodological approach poses model-based principles, including option and contract models, jointly with game theory elements.
Royalty Lease Evaluation (RLE) distillation analysis was performed on six hundred (600) wells in Petrotrin's Soldado acreage. This data has been traditionally generated for use by Petrotrin's refinery to determine if the crude oil feedstock is compatible to the refinery configuration or if the crude oil could cause yield, quality and production problems. These made for refinery reports have become part of Petrotrin's legacy data. The authors decided to examine this dormant dataset to ascertain what hidden stories it may tell about the oilfields from which they came.
In this investigation no data is generated, but an existing and dormant dataset will be analysed. Several components in a RLE distillation report on crude oil samples will be observed for trends, patterns and relationships. Ternary diagrams and cross-plots will be employed. Specific geochemical revelations from the RLE data will be validated by comparison to conventional gas chromatography data.
This investigation will illustrate how evaporative fractionation, which is a later charge of light hydrocarbons mixing with an emplaced biodegraded oil is evidenced by a phenomenon called the" Gas Oil Anomaly", seen in the RLE data. Essentially this is the absence of any gas oil fraction combined with the presence of light hydrocarbons in the distillation data. It will also be demonstrated that presence of the later charge of light hydrocarbons has been the key factor in the prolific production from the Soldado reservoirs.
Additional analysis of the light oil and gas oil fractions of a crude oil will reveal properties and characteristics that suggest there were different sources for both the originally emplaced oils and the later charge of light hydrocarbons. The data also shows that due to the evaporative fractionation phenomenon there is no correlation with API Gravity, oil viscosity, Sulphur content and depth of the reservoirs in Soldado. It will also be demonstrated that the data can be used as a qualitative tool leading to exploration plays in the Soldado acreage.
Explorationists at Petrotrin will find the results of this investigation to be both useful and provocative as it directs their attention to specific Trinmar Soldado oilfields as deep exploration play areas in a manner that traditional geochemical analyses have not been able to. It also allows the practioners in the Petrotrin Soldado acreage to better understand the productivity and complex fluid distributions in the Soldado reservoirs.
Balaji, Karthik (University of North Dakota) | Rabiei, Minou (University of North Dakota) | Canbaz, Hakan (Schlumberger) | Agharzeyva, Zinyat (Texas A & M University) | Tek, Suleyman (University of the Incarnate Word) | Bulut, Ummugul (Texas A&M University-San Antonio) | Temizel, Cenk (Aera Energy LLC)
Data-driven methods serve as a robust tool to turn data into knowledge. Historical data generally has not been used in an effective way in analyzing processes due to lack of a well-organized data, where there is a huge potential of turning terabytes of data into knowledge. With the advances and implementation of data-driven methods data-driven models have become more widely-used in analysis, predictive modeling, control and optimization of several processes. Yet, the industry overall is still skeptical on the use of datadriven methods, since they are data-based solution rather than traditional physics-based solutions; even though physics and geology are sometimes part of this methodology. This study comprehensively evaluates the status of data-driven methods in oil and gas industry along with the recent advances and applications.
This study outlines the development of these methods from the fundamentals, theory and applications of these methods along with their historical acceptance and use in the industry. Major challenges in the process of implementation of these methods are reviewed for different areas of applications. The major advantages and drawbacks of data-driven methods over the traditional methods are discussed. Limitations and areas of opportunities are outlined. Latest advances along with latest applications and the associated results and value of the methods are provided.
It is observed that the successful use of data-driven methods requires strong understanding of petroleum engineering processes and the physics-based conventional methods together with a good grasp of traditional statistics, data mining, artificial intelligence and machine learning. Data-driven methods start with a data-based approach to identify the issues and their solutions. Even though data-driven methods provide great solutions on some challenging and complex processes, that are new and/or hard to define with existing conventional methods, there is still skepticism in the industry on the use of these methods. This is strongly tied to the delicacy and sensitive nature of the processes and on the usage of the data. Organization and refinement of the data turn out to be important components of an efficient data-driven process.
Data-driven methods offer great advantages in the industry over that of conventional methods under certain conditions. However, the image of these methods for most of the industry professionals is still fuzzy. This study serves to bridge the gap between successful implementation and more widely use and acceptance of data-driven methods, and the fuzziness and reservations on the understanding of these methods in the industry. Significant components of these methods along with clarification of definitions, theory, application and concerns are also outlined in this study.
Kumagai, Hidenori (JAMSTEC) | Nozaki, Tatsuo (JAMSTEC) | Ishibashi, Jun-ichiro (Kyushu University) | Saito, Saneatsu (JAMSTEC) | Komori, Shogo (AIST) | Hamada, Yohei (JAMSTEC) | Sanada, Yoshinori (JAMSTEC) | Saruhashi, Tomokazu (JAMSTEC) | Maeda, Lena (JAMSTEC) | Kubo, Yu ’usuke (JAMSTEC) | Takai, Ken (JAMSTEC)
A series of scientific drilling at the submarine hydrothermal fields were conducted to decipher mineralization process of the hydrothermal deposits in the middle Okinawa Trough. By using LWD technique, in-situ measurements of temperature, flow-in of the fluid, electromagnetic nature in the boreholes were successfully achieved. Further, the physical properties of the drilled formations showed good agreement with those of cored samples analyzed on-board and shore-based.
Submarine ore-bodies recently attract broad interest among governmental, industrial, academic communities under circumstances that any activity directing sustainable development is desired. Following this stream of the trend, several countries and companies applied properties of submarine mining even in distant high-seas far away from the shorelines.
Thus in Japan, within the eleven governmental funded R&D projects under an umbrella of SIP, a project focused on submarine resources named as ”Next-Generation Technology for Ocean Resources Exploration (Zipangu in the Ocean)” has been launched in 2014. This project not only focuses hardware developments to be utilized in exploration of the submarine resources but also does scientific studies of formation processes of submarine resources and assessment technique for ecological impacts. In the project, hydrothermal sulfide deposits is mainly targeted among three types of submarine resources besides Fe-Mn oxide crusts enriched in Co or REY-rich mud.
Even though such situation, there are still large arguments on the formation model of the submarine hydrothermal deposits (e.g. Tornos et al., 2015 and references therein), especially on those having large volumes of the consealed type, i.e. ore bodies buried beneath the seafloor.
Prior to the commencement of the “Zipangu in the Ocean” project, the IODP Expedition 331 scientific drilling was conducted in 2010. During the expedition, an occurrence of vast sub-seafloor hydrothermal fluid reservoir was suggested beneath the Iheya-North Knoll, Okinawa Trough (Takai et al., 2012). Further, a seismic reflection analyses suggests that such a reservoir may extend a kilometer area indicated as a reverse polarity reflector (Tsuji et al., 2012). This view is also supported by dense heat flow measurement on the Knoll (Masaki et al., 2011). In the expedition, the heterogeneous sub-seafloor nature beneath the hydrothermally active area prohibited the core samples from being retrieved in high yield, down to a few percent in the holes (Takai et al., 2012), which is critical shortcomings to establish the model of the ore genesis.
The Parque das Conchas (BC10) field offshore Brazil, operated by Shell and owned together with ONGC and QPI, has challenging reservoir conditions. Several subsea fields with viscosities ranging from 1 to 900 cP and gas volume fractions between 5% and 70% require subsea boosting to lift production fluids to the FPSO facility. Since first oil in 2009, a unique method of subsea separation and boosting has been deployed on BC-10, utilizing vertical caisson separators with Electrical Submersible Pumps (ESP's) to pump well fluids from up to 2000m water depth to the FPSO facility. Maintenance of the ESP assemblies requires an intervention using a MODU (Mobile Offshore Drilling Unit).
Shell pursued an alternative subsea boosting solution using Mudline Pump (MLP) technology, with the objective to reduce field Opex and increase redundancy. The MLP was conceived as a retrofit module, which was to be fully compatible with the existing infrastructure. This includes using existing variable frequency drives, high voltage umbilicals, subsea mechanical interfaces, controls, hydraulics, and chemical injection. Despite the prior development of a 3 MW (megawatt) MudLine Pump (MK1), the specifics of the BC10 application required further development and qualification. The design pressure was increased from 5,000 psi to 7,500 psi, which required requalification of motor and barrier fluid circuit components. Additionally, the challenging multiphase flow conditions led to the development of an innovative control strategy to maximise the production window, whilst ensuring safe operating conditions for the pump within the existing system constraints.
This paper is to represent reviews of low dosage hydrate inhibitor's (LDHI) evolution and advances, and to provide a general guide for LDHI considerations, historically, hydrate risk has been managed by keeping the fluids warm, removing water, and/or by injecting thermodynamic hydrate inhibitors (THI), commonly methanol or glycol. THIs require high dosage rate therefore production systems can reach a treatment limited by supply, storage, and umbilical injection constraints. Besides, high dosage of MeOH can cause crude contamination for downstream refineries, which may result in penalty.
Over last two decades LDHIs have been extensively researched and developed as an alternative hydrate management chemical for oil and gas industry. LDHIs are divided into two main categories; Kinetic Hydrate Inhibitor (KHI) and Anti-Agglomerant (AA), both have been successfully used in field applications, but each comes with their unique challenges for applications, OPEX and CAPEX considerations. LDHIs have proven track records in numerous fields in their performance, either as stand-alone chemical treatment or reducing amounts of methanol/glycol usage, which has directly resulted in CAPEX and OPEX reduction. LDHIs have been instrumental in managing risks of early water breakthrough, high cost of THI storage and transportation, HSSE concerns around THI handling, and undersized pump capacity for required chemical volumes. Switching to LDHIs also offers an economic advantage by reducing umbilical line diameter. Latest advances in the LDHI technology is breaking barriers and pushing limits.
The paper summarizes historical advancements in LDHIs over the last two decades, discusses application advantages and limitations, and the criterions to consider for selecting LDHIs.
On November, 2010 Petrobras defined the necessity of one additional gas export pipeline in Santos Basin Pre-Salt area to improve the capacity of the export gas network and assure the objectives defined in the Strategic Plan. Nowadays there are two gas export pipelines in operation to export the gas from pre-salt area: Rota 1 connecting Lula Sul field to onshore facilities in Caraguatatuba/SP and Rota 2 connecting Lula Área de Iracema Sul to onshore facilities in Cabiunas/RJ.
The new 20-in and 24-in gas export pipeline named Rota 3 is approximately 307km long and connects Lula Norte field in Santos Basin to Jaconé Beach/Maricá It has 15 spare hubs and 3 PLEMs for future connections to Sépia, Berbigão, Atapu, Sururu, Buzios and Libra fields. Also, Rota 3 is interconnected to export gas pipeline Rota 2 in a loop to permit gas exportation through Maricá and Cabiúnas.
This paper addresses the pipeline design optimizations based on standard DNV-0S-F101 and on several consulting to national and international pipe suppliers. Full scale qualifications tests were performed in accordance with DNV-0S-F101 to permit the use of the alfafab factor identical to one for the supplied 20-in UOE pipes. All qualification process was witnessed by DNV.
Additional simplifications were introduced aiming to costs reduction and in order to improve attractiveness of EPCI (Engineering, Procurement, Construction and Installation) contract. Installation contractors were invited to suggest simplifications to the project.
Lessons learned during the design, BID process and installation phase of the project are also envisaged.
Formation tops is one of the important information that is gathered during the exploration and delineation phase. This valuable information aids in setting the casing properly during the development phase and ensure proper zonal isolation between different zones. Every time a new well is drilled, actual formation tops are picked using various methods such as rate of penetration (ROP) charts, gamma ray (GR), formation cuttings and mud logging. These data are used in updating the geological model and in ensuring a proper zonal isolation in critical sections. Each of these methods has its own advantages and limitations such as cost, accuracy, and man power. Most of these methods suffer from a lag in time or depth which prevents the formation tops from being picked instantaneously.
The goal of this paper is to introduce a better method for picking formation tops. It can be a potential alternative to replace other more expensive techniques. The new technique involves the use of drilling mechanical parameters along with the rate of penetration to increase the accuracy of prediction. This will help to detect a true increase or decrease in ROP even if the drilling parameters are fluctuating.
Field data were gathered from two wells with the same bit size and the same formation type. The data were screened and cleaned from any outliers or noise using six different algorithms while retaining the data quality and representation. Using six inputs and four outputs, 30 different sensitivity analyses were conducted including using artificial neural network (ANN) to achieve the best results and prediction accuracy. Well-A was used to train and test the data with 70/30 ratio, while well-B was totally unseen data.
The results obtained showed that ANN can predict formation tops with great accuracy. The best result was found using ANN with 20 neurons and one layer in which correlation of coefficient (R) was 0.94 and 0.98 for both wells. With this new technique, detecting formation changes will be faster compared to other methods since no logs have to be processed and nor any wait is required for cuttings to reach the surface. The formations can therefore be picked in real-time with good accuracy at almost no extra costs because it uses the real-time data which is already available.
Rate of Penetration referrers to the speed of breaking the rock under the bit. It measures the speed or the progress of the bit when it drills the formation. It has been reported in the industry that high percentage of the well budget is spent on the drilling phase, thus many drilling operators pay close attention to this factor and try to optimize it as much as possible. However, it is very challenging to capture the effect of each individual parameter since most of them are interconnected, and changing one parameter affects the other. As a result, many companies maintain a data for the drilling performance per field and set certain benchmarks to gauge the speed of any newly drilled well. To date, no solid or reliable model exists because of the complexity of the drilling process, and one cannot capture every factor to predict the rate of penetration. Therefore, the utilization of artificial intelligence (AI) in the drilling applications will be a game changer since most of the unknown parameters are accounted for during the modeling or training process.
The objective of this paper is to develop a rate of penetration model using artificial neural network (ANN) with the least possible number of inputs. Actual field data of more than 4,500 data points were used to build the model. The inputs were pumping rate, weight on bit, rotation speed, torque, stand pipe pressure and unconfined compressive strength. Well-A was used to train and test the model with 70/30 data ratio. Then two unseen data which are well-B and well-C were used to test the model. ANN was used in this study, with many sensitivity analyses to achieve the best combination of parameters.
The obtained results showed that ANN can be used effectively to predict the rate of penetration with average correlation coefficient of 0.94 and average absolute percentage error of 8.6%, which shows 22% improvement over the current published methods. The best ANN model was achieved using 1 layer, 12 neurons and a linear transfer function. The developed ANN-ROP model proved to be successful using only six inputs and having a total of two wells with unseen data.
Rate of Penetration referrers to the speed of breaking the rock under the bit. It measures the speed or the progress of the bit when it drills the formation, and in field units it is reported in ft/hr. It has been reported in the industry that 50% of the well budget is spent on the drilling phase, thus many drilling operators pay close attention to this factor and try to optimize it as much as possible. However, it is very challenging to capture the effect of each individual parameter since most of them are interconnected, and changing one parameter affects the other. As a result, many companies maintain a data for the drilling performance per field and set certain KPIs to gauge the speed of any newly drilled well.