Dynamic Formation Evaluation to Reduce Uncertainty and Confirm Completed Intervals in Brown Fields

2021 ◽  
Author(s):  
Muhamad Aizat Kamaruddin ◽  
Ayham Ashqar ◽  
Muhammad Haniff Suhaimi ◽  
Fairus Azwardy Salleh
Keyword(s):  
Real Time ◽  
Optical Sensors ◽  
Sensor Technology ◽  
Innovative Technology ◽  
Fluid Type ◽  
Formation Evaluation ◽  
Reservoir Fluid ◽  
Logging While Drilling ◽  
Dynamic Formation

Abstract Uncertainties in fluid typing and contacts within Sarawak Offshore brown field required a real time decision. To enhance reservoir fluid characterisation and confirm reservoir connectivity prior to well final total depth (TD). Fluid typing while drilling was selected to assure the completion strategy and ascertain the fluvial reservoir petrophysical interpretation. Benefiting from low invasion, Logging While Drilling (LWD) sampling fitted with state of ART advanced spectroscopy sensors were deployed. Pressures and samples were collected. The well was drilled using synthetic base mud. Conventional logging while drilling tool string in addition to sampling tool that is equipped with advanced sensor technology were deployed. While drilling real time formation evaluation allowed selecting the zones of interest, while fluid typing was confirmed using continually monitored fluids pump out via multiple advanced sensors, contamination, and reservoir fluid properties were assessed while pumping. Pressure and sampling were performed in drilling mode to minimise reservoir damage, and optimise rig time, additionally sampling while drilling was performed under circulation conditions. Pressures were collected first followed by sampling. High success in collecting pressure points with a reliable fluid gradient that indicated a virgin reservoir allowed the selection of best completion strategy without jeopardising reserves, and reduced rig time. Total of seven samples from 3 different reservoirs, four oil, and three formation water. High quality samples were collected. The dynamic formation evaluation supported by while drilling sampling confirmed the reservoir fluid type and successfully discovered 39ft of oil net pay. Reservoir was completed as an oil producer. The Optical spectroscopy measurements allowed in situ fluid typing for the quick decision making. The use of advanced optical sensors allowed the sample collection and gave initial assessment on reservoir fluids properties, as a result cost saving due to eliminating the need for additional Drill Stem Test (DST) run to confirm the fluid type. Sample and formation pressures has confirmed reservoir lateral continuity in the vicinity of the field. The reservoir developed as thick and blocky sandstone. Collected sample confirmed the low contamination levels. Continuous circulation mitigated sticking and potential well-control risks. This is the first time in surrounding area, advanced optical sensors are used to aid LWD sampling and to finalize the fluid identification. The innovative technology allowed the collection of low contamination. The real-time in-situ fluid analysis measurement allowed critical decisions to be made real time, consequently reducing rig downtime. Reliable analysis of fluid type identification removed the need for additional run/service like DST etc.

In-Situ Diagnosis of Formation Characteristics in Horizontal Wells

2005 ◽  
Vol 8 (05) ◽  
pp. 445-451
Author(s):  
Huanwen Cui ◽  
Yannong Dong ◽  
Shekhar Sinha ◽  
Rintu Kalita ◽  
Younes Jalali
Keyword(s):  
Boundary Condition ◽  
Relative Permeability ◽  
Direct Contact ◽  
Horizontal Wells ◽  
Productivity Index ◽  
Formation Evaluation ◽  
Sensing Technology ◽  
Dynamic Formation

Summary A method is presented for estimating the distribution of a parameter related to the productivity index along the length of a liner-completed horizontal well, using measurements of well flowing pressure at multiple points along the path of flow in the wellbore. This is the concept of near-wellbore diagnosis with multipoint pressure measurements, which in principle can be made with fiber-optic sensors. The deployment mechanism of the sensors is not modeled in this study, although the temperature version of such sensors has been deployed in horizontal wells on an extended-tail-pipe or stinger completion. (The temperature sensors also have been deployed in horizontal wells with sand-screen completions, in direct contact with the formation, but that configuration is not investigated in this study.) The parameter that is estimated is known in reservoir-simulation terminology as the connection factor (CF), which represents the hydraulic coupling or connectivity between the reservoir and the wellbore (between formation gridblocks and well segments). Parameter CF has units of md-ft, similar to flow capacity, or productivity index multiplied by viscosity. Specifically, the parameter is directly proportional to the geometric mean of the permeability perpendicular to the horizontal axis of the well and is inversely related to skin. No attempts are made in this study to estimate these parameters individually, which may require recourse to other methods of well diagnosis(e.g., dynamic formation testing, transient analysis, and production logging). The method applies to flow under constant-rate conditions and yields estimates of the CF, which represents the quality of the formation in the vicinity of the well and the integrity of the completion along the well trajectory. The quality of the inversion is determined by the spatial density and accuracy of the multipoint measurements. Inversion quality also depends on knowledge of the wellbore hydraulic characteristics and the relative permeability characteristics of the formation. The basic configuration investigated in this study consists of a five-node pressure array in a 2,000-fthorizontal well experiencing a total pressure drop of approximately 60 psi when produced at 10,000 STB/D. A reasonable estimate of the distribution of the parametric group CF is obtained even when allowing for measurement drift and errors in liner roughness and relative permeability exponent. Also, the inversion can be rendered insensitive to knowledge of the far-field permeability through a scaling technique. Therefore, good estimates of the near-wellbore CF profile can be obtained with uncertain knowledge of the reservoir permeability field. This is important because the technique can be applied not only to early-time but also to late-time data. The application of the multipoint pressure method is illustrated through a series of examples, and its potential for near-wellbore formation evaluation for horizontal wells is described. Introduction Horizontal wells can be diagnosed on the basis of information derived from openhole and cased-hole surveys. These include petrophysical logs, dynamic formation testers, production logging, and pressure-transient testing. With the advent of permanent sensing technologies and the development of methods of production-data inversion or history matching, a new form of cased-hole diagnosis can be envisaged, with improved spatial and temporal coverage and without the need for in-well intervention and interruption of production. The impact of such methods on reservoir-scale characterization can also be significant. There are two main preconditions for the development of such a methodology, one concerning sensing technology and the other concerning interpretation methodology. Permanent sensing technology has made great progress during the last decade, with the development of single-point and distributed measurements that can be deployed with the completion (pressure, flow rate, and distributed temperature). However, these systems are typically developed as stand alone measurement units and do not enjoy the required degree of integration. Current modeling methods, however, can be used to provide an incentive for such integration. The well-diagnosis problem is decoupled in our investigation into diagnosis of flow condition in the wellbore and diagnosis of near-wellbore formation characteristics. (By "near-wellbore," we mean the wellbore gridblock scale.)This is partly to adhere to the conventional demarcation between production logging and dynamic formation evaluation and partly to show the natural consequence of the mathematical problem. Basically, the wellbore-diagnosis problem (determination of flux distribution, as in production logging) can treat the formation simply as a boundary condition, but the formation-evaluation problem cannot do the same (i.e., treat the wellbore interface as a boundary condition) because evaluation is based on measurements made inside the wellbore. Thus, both the wellbore and the formation have to betaken into account. (Sensors that are in direct contact with the formation, as mentioned in the Summary, are emerging.8 Therefore, the evolution of this problem is to be expected.) In this study, the permanent or in-situ analog of dynamic formation evaluation is investigated. The in-situ analog of production logging is investigated in a parallel study.

New Advances in Surface Data Logging Technologies for Comprehensive Real-Time Petrophysical Evaluation to Optimize Logging Programs in a Mature Field; A Case History, Onshore, Abu Dhabi

2021 ◽  
Author(s):  
Saif Al Arfi ◽  
Mohamed Sarhan ◽  
Olawole Adene ◽  
Muhammad Rizky ◽  
Agung Baruno ◽  
...  
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Gas Analysis ◽  
Data Logging ◽  
Fully Integrated ◽  
Formation Evaluation ◽  
X Ray ◽  
Reservoir Fluid ◽  
Surface Data ◽  
Mud Logging

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.

scholarly journals The aquatic real-time monitoring network; in-situ optical sensors for monitoring the nation's water quality

Fact Sheet ◽  
2011 ◽  
pp. 1-2 ◽  
Author(s):  
Brian A. Pellerin ◽  
Brian A. Bergamaschi ◽  
Peter S. Murdoch ◽  
Bryan D. Downing ◽  
John Franco Saraceno ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Optical Sensors ◽  
Monitoring Network ◽  
Real Time Monitoring

Analyzing Reservoir Fluid Composition In-Situ in Real Time: Case Study in a Carbonate Reservoir

2003 ◽  
Author(s):  
Fujisawa Go ◽  
Oliver C. Mullins ◽  
Chengli Dong ◽  
Andrew Carnegie ◽  
Soraya S. Betancourt ◽  
...  
Keyword(s):  
Real Time ◽  
Carbonate Reservoir ◽  
Fluid Composition ◽  
Reservoir Fluid
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