Improved Integrated Reservoir Interpretation Using Gas While Drilling Data

2001 ◽  
Vol 4 (06) ◽  
pp. 489-501 ◽  
Author(s):  
D. Kandel ◽  
R. Quagliaroli ◽  
G. Segalini ◽  
B. Barraud

Summary The acquisition of gas in mud data while drilling for geological surveillance and safety is an almost universal practice. This source of data is only rarely used for formation evaluation because of the widely accepted presumption that it is unreliable and unrepresentative. Recent developments in the mud-logging industry to improve gas data acquisition and analysis have led to the availability of better quality data. Within a joint Elf/Eni-Agip Div. research program, a new interpretation method has been developed following the comprehensive analysis and interpretation of gas data from a wide range of wells covering different types of geological, petroleum, and drilling environments. The results, validated by correlation and comparison with other data such as logs, well tests, and pressure/volume temperature (PVT) data, enable us to characterize lithological changes; porosity variations and permeability barriers; seal depth, thickness, and efficiency; gas diffusion or leakage; gas/oil and hydrocarbon/water contacts; vertical changes in fluid over a thick monolayer pay zone; vertical fluid differentiation in multilayer intervals; and biodegradation. The comparison of surface gas, PVT, and geochemistry data clearly confirms the consistency between the drilling gas data (gas shows) and the corresponding reservoir fluid composition. The near real-time availability, at no extra acquisition cost, of such data has led to:The optimization of future well operations (such as logging and testing).A better integration of while-drilling data to the well evaluation process.A significant improvement in both early formation evaluation and reservoir studies, especially for the following applications, in which traditional log analysis often remains inconclusive:Very-low-porosity reservoirs.Thin beds.Dynamic barriers and seal efficiency.Low-resistivity pay.Light hydrocarbons. Examples show gas while drilling (GWD) wellsite quicklook interpretations with simple lithological and fluid interpretations, as well as more complex reservoir and fluid characterization applications in varied geographical and geological contexts; both demonstrate how GWD data are integrated with more standard data sets. Introduction The measurement of gas shows is standard practice during the drilling of exploration and development wells. Continuous gas monitoring sometimes enables us to indicate, in general terms, the presence of hydrocarbon-bearing intervals, but it rarely allows us to define the fluid types (oil, condensate and/or gas, and water). Gas data are at present largely underused because they are considered unreliable and not fully representative of the formation fluids. There are many reasons for this. On one hand, poorly established correlations exist between reservoir fluids and shows at surface; on the other hand, numerous drilling parameters strongly influence the recorded gas data, such as formation pressure, mud weight and type, gas-trap position in the shaker ditch, and mud-out temperatures. One reason may be the very low cost of such data, often equated with low value. Until a few years ago, the analysis performed on gas shows was generally restricted to the use of Pixler and/or Geoservices diagrams (or equivalent), wetness, balance, character, and gas normalization.1–4 Recent improvements in gas-acquisition technology and the new GWD methodology allow us to perform reservoir interpretation in near real time for fluid identification and contacts [oil/water contact (OWC), gas/oil contact (GOC), etc.], lithological changes, and barrier efficiency, thus allowing operations optimization (e.g., coring, wireline recording and sampling, and testing operations). It is also possible to integrate the GWD interpretation in reservoir, geochemical, PVT analysis, and comprehensive studies. Method Data Acquisition. The measurement of gas shows in the circulating drilling mud was introduced in the early days of mud logging (ML) with two objectives: first, as a safety device to indicate well behavior to drillers, and second, as an indicator of hydrocarbon-bearing zones. Today, gas-shows measurement is systematically acquired in the petroleum industry for the same reason, but it is seldom used to its full potential, mainly because of an ongoing prejudice that the data are not representative of the formation fluids and/or that the recording of these data is strongly influenced by varying drilling parameters. The ML gas system is composed of three parts:A "gas trap" to extract gas from the mud stream situated somewhere between the bell nipple and the shaker box (often in the latter).Lines, pumps, and filters enabling the transport of a dry-gas sample to the ML unit.A detection system in the ML unit. Recent efforts in the mud-logging industry to improve gas-data acquisition and analysis have led to the availability of better quality data, which has provided reliable lithological and fluid information since the 1990s. In the 1980s, most of the ML companies introduced the flame ionization detectors (FID) to replace previous total gas (TG) and chromatograph measurements. The TG measurement gives the total amount of hydrocarbon components extracted from the mud and burned in the detector. The TG could now be correlated with the C1-C5 readings from the new breed of chromatographs.5 Finally, over the past few years, several ML companies have introduced fast-gas chromatographs with improved resolution (C1-C5 in less than 1 minute), improved C1/C2 separation, and, above all, improved reliability and repeatability. High-speed chromatographs using a thermal-conductivity detector have also appeared on the market, but they were not tested within this project. Work carried out by Texaco in the early 1990s led to a significant improvement in basic trap design with the introduction of the quantitative gas measurement (QGM) trap, which was a major step in reducing the effect of environmental changes.6 An alternative proposition from Geoservices was to replace the trap, generally situated in the shaker box, with a pumping system supplying the trap with a constant volume of mud sucked from a probe situated close in the flowline to the bell nipple.7

2021 ◽  
Author(s):  
Temirlan Zhekenov ◽  
Artem Nechaev ◽  
Kamilla Chettykbayeva ◽  
Alexey Zinovyev ◽  
German Sardarov ◽  
...  

SUMMARY Researchers base their analysis on basic drilling parameters obtained during mud logging and demonstrate impressive results. However, due to limitations imposed by data quality often present during drilling, those solutions often tend to lose their stability and high levels of predictivity. In this work, the concept of hybrid modeling was introduced which allows to integrate the analytical correlations with algorithms of machine learning for obtaining stable solutions consistent from one data set to another.


2011 ◽  
Vol 51 (1) ◽  
pp. 259
Author(s):  
Rajesh Trivedi ◽  
Shripad Biniwale ◽  
Adil Jabur

With a vision of innovation, integrity and agility, Nexus Energy began first production of Longtom field in October 2009. The Longtom gas field is located in the Gippsland Basin, offshore Victoria where the produced gas is transported to Santos’ Patricia Baleen gas processing plant. All production data is acquired by Santos with the supervisory control and data acquisition (SCADA) system. The challenge for Nexus Energy was to monitor the field remotely in the absence of a data historian and to support the operational people proactively. Data acquisition from Santos, validation, and storage in a secured centralised repository were therefore key tasks. A system was needed that would not only track accurate production volumes to meet the daily contractual quantity (DCQ) production targets but that would also be aligned with Nexus’s vision for asset optimisation. We describe how real-time data is acquired, validated, and stored automatically in the absence of a data historian for Longtom field, and how the deployed system provides a framework for an integrated Production Operation System (iPOS). The solution uses an integrated methodology that allows effective monitoring of real-time data trends to anticipate and prevent potential well and equipment problems, thus assisting in meeting DCQ targets and providing effective analysis techniques for decision making. Based on full workflow automation, the system is deployed for acquisition, allocation, reporting and analysis. This has increased accuracy, accountability and timely availability of quality data, which has helped Nexus improve productivity. The comprehensive reporting tool provides access to operational and production reports via email for managers, output reports in various formats for joint venture partners, and nontechnical users without direct access to the core application. A powerful surveillance tool, integrated with the operational database, provides alarms and notifications on operation issues, which helps engineers make proactive operational decisions. The framework allows a streamlined data flow for dynamic updates of well and simulation models, improving process integration and reducing the runtime cycle.


2021 ◽  
Author(s):  
Saif Al Arfi ◽  
Mohamed Sarhan ◽  
Olawole Adene ◽  
Muhammad Rizky ◽  
Agung Baruno ◽  
...  

Abstract The challenges of drilling new wells are increasingly associated with minimizing HSE risks, that relate to chemical radioactive sources in the Bottom Hole Assembly for formation evaluation. Drilling risks such as differential sticking, also necessitates investigation of alternative petrophysical data gathering methodologies that can fulfil these requirements. Surface Data Logging presents a viable alternative in mature fields, satisfying petrophysical data gathering and interpretation in real-time as well, as traditional geological applications and offset well correlations in a way, to optimize well construction costs. During the planning phase, a fully integrated approach was adopted including advanced cutting and advanced gas analysis to be deployed, in this case study, well together with experienced well site personnel. A comprehensive pre-well study was conducted reviewing all offset nearby wells data. The workflow included provision of full real-time advanced cuttings and gas analysis for formation evaluation and reservoir fluid composition, lithology description, and addressing effective hole cleaning concerns. The advanced Mud Logging services was run in parallel to the Logging While Drilling services for a few pilot wells, in order to correlate downhole tool parameters, with respect to data quality control, to identify the petrophysical character of the formation markers for benchmarking future data gathering requirements. In addition to the potential use of standalone fully integrated advanced Mud Logging to reduce risks and minimize field development costs. With the help of experienced wellsite geologist on location and real time advanced gas detection utilizing high resolution mass spectrometer and X-Ray fluorescence (XRF) and X-Ray Diffraction (XRD) data, geological boundaries and formations tops were accurately identified across the whole drilled interval. Modern and advanced interpretation techniques for the integrated analysis were proven to be effective in determining sweet spots of the reservoir, fluid type, and overall reservoir quality. Deployment of fully integrated mud logging solutions with new interpretation methodologies can be effective in providing a better understanding of reservoir geological and petrophysical characteristics in real-time, offering viable alternative for minimizing formation evaluation sensors in the BHA, particularly eliminating radioactive sources, while reducing overall developments costs, without sacrificing formation evaluation requirements.


2013 ◽  
Vol 712-715 ◽  
pp. 1983-1986
Author(s):  
Yin Liu ◽  
Du Feng Li ◽  
Guo Hong Cao ◽  
Sheng Li Tian ◽  
Cheng Liu

A set to the system is designed for detecting the drilling rig hydraulic system. In the system, the significant indicators of drilling parameters are collected, which include hydraulic oil temperature, pressure values of some important points and number of the bubble in the hydraulic oil. All data from sensors is real time displayed.So those faults are detected in time.


2021 ◽  
pp. 1-13
Author(s):  
Hany Gamal ◽  
Ahmed Alsaihati ◽  
Salaheldin Elkatatny

Abstract The sonic data provides significant rock properties that are commonly used for designing the operational programs for drilling, rock fracturing, and development operations. The conventional methods for acquiring the rock sonic data in terms of compressional and shear slowness (ΔTc and ΔTs) are considered costly and time-consuming operations. The target of this paper is to proposed machine learning models for predicting the sonic logs from the drilling data in real-time. Decision tree (DT) and random forest (RF) were employed as train-based algorithms for building the sonic prediction models for drilling complex lithology rocks that have limestone, sandstone, shale, and carbonate formations. The input data for the models include the surface drilling parameters to predict the shear and compressional slowness. The study employed data set of 2888 data points for building and testing the model, while another collected 2863 data set was utilized for further validation for the sonic models. Sensitivity investigations were performed for DT and RF models to confirm optimal accuracy. The correlation of coefficient (R), and average absolute percentage error (AAPE) were used to check the models' accuracy between the actual values and models` outputs, in addition to, the sonic log profiles. The results indicated that the developed sonic models have a high capability for the sonic prediction from the drilling data as DT model recorded R higher than 0.967 and AAPE less than 2.76% for ΔTc and ΔTs models, while RF showed R higher than 0.991 with AAPE less than 1.07%. The further validation process for the developed models indicated the great results for the sonic prediction and RF model outperformed DT models as RF showed R higher than 0.986 with AAPE less than 1.12% while DT prediction recorded R greater than 0.93 with AAPE less than 1.95%. The sonic prediction through the developed models will save the cost and time for acquiring the sonic data through the conventional methods and will provide real-time estimation from the drilling parameters.


2021 ◽  
Author(s):  
Meor M. Meor Hashim ◽  
M. Hazwan Yusoff ◽  
M. Faris Arriffin ◽  
Azlan Mohamad ◽  
Tengku Ezharuddin Tengku Bidin ◽  
...  

Abstract The advancement of technology in this era has long profited the oil and gas industry by means of shrinking non-productive time (NPT) events and reducing drilling operational costs via real-time monitoring and intervention. Nevertheless, stuck pipe incidents have been a big concern and pain point for any drilling operations. Real-time monitoring with the aid of dynamic roadmaps of drilling parameters is useful in recognizing potential downhole issues but the initial stuck pipe symptoms are often minuscule in a short time frame hence it is a challenge to identify it in time. Wells Augmented Stuck Pipe Indicator (WASP) is a data-driven method leveraging historical drilling data and auxiliary engineering information to provide an impartial trend detection of impending stuck pipe incidents. WASP is a solution set to tackle the challenge. The solution is anchored on Machine Learning (ML) models which assess real-time drilling data and compute the risk of potential stuck pipe based on drilling activities, probable stuck pipe mechanisms, and operation time. The output of the analysis is built on a warning and alarm system that can be utilized by the engineers to refine and optimize the well construction activities; tackling the stuck pipe issue before it manifests. This solution is evaluated by comparing historical and real-time drilling parameters with the prediction data to generate an error analysis. On top of that, a confusion matrix is tabulated based on the analysis of warnings and alarms raised by the solution to rule out Type 1 and Type 2 errors. The WASP solution has demonstrated tolerably accurate predictions of drilling parameters with minimal warnings and alarms error. With the solution, the stuck pipe issue can be identified hours earlier before the actual stuck pipe was reported in the historical well. It is a powerful tool with the capability to pinpoint possible stuck pipe mechanisms for engineer's immediate analysis and intervention. Value creation from the WASP solution has been massive with a reduction in manhours of analysis, potential NPT events, and unexpected operational costs. Data-driven techniques are effective in preventing stuck pipe incidents and will be scalable to tackle other downhole issues such as loss of circulation, well control, and borehole instability.


2021 ◽  
Author(s):  
Stephen McCormick ◽  
Rajesh Thatha ◽  
Martin Leonard ◽  
Samuel Escott ◽  
Adam Sedgwick ◽  
...  

Abstract Obtaining high resolution, quality formation evaluation data is still only possible with wireline logging. However, with the continued push into deeper and more complex drilling environments, many challenges have been placed in the way of wireline logging, including high tension, high deviation, and increased differential pressure. These factors contribute to an increased risk of tool sticking incidents and lost-in-hole scenarios. Several methods of mitigating these issues on surface (powered capstans, pipe conveyance, etc) have been implemented in the past, but none have been successful in reducing or eliminating the risk downhole without introducing further drawbacks. This paper describes how a new wireline conveyance system has eliminated these issues. The conveyance system consists of wheeled carriages that carry the toolstring off-centre. The mass of the toolstring acts as a counterweight to ensure correct tool orientation in the wellbore. This orientation feature also enables a "guide" device to help navigate ledges and washouts. Such a system eliminates toolstring hold ups, allows access to highly deviated wells without pipe conveyance or tractors, and significantly mitigates differential sticking hazards, while also offering additional benefits in operational efficiency and data quality. A case study from a particularly difficult well in New Zealand is presented. Data acquisition in this well was fraught with challenges: In addition to the 2000m tangent section at 67° deviation, well had severe borehole breakouts. Previous experience in similar scenarios with conventional data acquisition methods yeided poor results. The wheeled carriage system was deployed in multiple innovative configurations resulting in the acquisition of excellent quality data from five wireline descents in hole. This wireline conveyance system has been routinely deployed on multiple deepwater operations in the Gulf of Mexico. One such operation is presented where large gains in logging efficiency have been realised, particularly with the elimination of differential sticking risk and time-consuming pipe conveyed logging. The new technology takes a holistic approach to wireline tool conveyance: Prevent sticking issues using wheeled carriages and mitigate fishing risk using ultra-high strength wireline cables. Wheeled carriages greatly reduce the tool-borehole contact area, preventing the incidence of tool sticking. In addition, wheeled carriages reduce drag while ensuring optimum data quality by sensor position and orientation within the wellbore. Ultra-high strength cables provide ability to log at very high tensions and at the same time provide high overpull capability. The result is a safe, efficient, cost effective and complete Wireline data acquisition.


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