In-Situ Diagnosis of Formation Characteristics in Horizontal Wells
- Huanwen Cui (U. of Tulsa) | Yannong Dong (U. of Oklahoma) | Shekhar Sinha (Schlumberger) | Rintu Kalita (Schlumberger) | Younes Jalali (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- October 2005
- Document Type
- Journal Paper
- 445 - 451
- 2005. Society of Petroleum Engineers
- 5.5.8 History Matching, 5.5 Reservoir Simulation, 5.6.1 Open hole/cased hole log analysis, 5.6.11 Reservoir monitoring with permanent sensors, 5.3.2 Multiphase Flow, 5.1 Reservoir Characterisation, 2.3 Completion Monitoring Systems/Intelligent Wells, 5.2.1 Phase Behavior and PVT Measurements, 3.3.1 Production Logging, 5.6.3 Pressure Transient Testing, 3.3 Well & Reservoir Surveillance and Monitoring, 2.4.3 Sand/Solids Control, 3.2.2 Downhole intervention and remediation (including wireline and coiled tubing), 4.3.4 Scale
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A method is presented for estimating the distribution of a parameter relatedto the productivity index along the length of a liner-completed horizontalwell, using measurements of well flowing pressure at multiple points along thepath of flow in the wellbore. This is the concept of near-wellbore diagnosiswith multipoint pressure measurements, which in principle can be made withfiber-optic sensors. The deployment mechanism of the sensors is not modeled inthis study, although the temperature version of such sensors has been deployedin horizontal wells on an extended-tail-pipe or stinger completion. (Thetemperature sensors also have been deployed in horizontal wells withsand-screen completions, in direct contact with the formation, but thatconfiguration is not investigated in this study.)
The parameter that is estimated is known in reservoir-simulation terminologyas the connection factor (CF), which represents the hydraulic coupling orconnectivity between the reservoir and the wellbore (between formationgridblocks and well segments). Parameter CF has units of md-ft, similar to flowcapacity, or productivity index multiplied by viscosity. Specifically, theparameter is directly proportional to the geometric mean of the permeabilityperpendicular to the horizontal axis of the well and is inversely related toskin. No attempts are made in this study to estimate these parametersindividually, which may require recourse to other methods of well diagnosis(e.g., dynamic formation testing, transient analysis, and productionlogging).
The method applies to flow under constant-rate conditions and yieldsestimates of the CF, which represents the quality of the formation in thevicinity of the well and the integrity of the completion along the welltrajectory.
The quality of the inversion is determined by the spatial density andaccuracy of the multipoint measurements. Inversion quality also depends onknowledge of the wellbore hydraulic characteristics and the relativepermeability characteristics of the formation. The basic configurationinvestigated 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 whenproduced at 10,000 STB/D. A reasonable estimate of the distribution of theparametric group CF is obtained even when allowing for measurement drift anderrors in liner roughness and relative permeability exponent. Also, theinversion can be rendered insensitive to knowledge of the far-fieldpermeability through a scaling technique. Therefore, good estimates of thenear-wellbore CF profile can be obtained with uncertain knowledge of thereservoir permeability field. This is important because the technique can beapplied not only to early-time but also to late-time data. The application ofthe multipoint pressure method is illustrated through a series of examples, andits potential for near-wellbore formation evaluation for horizontal wells isdescribed.
Horizontal wells can be diagnosed on the basis of information derived fromopenhole and cased-hole surveys. These include petrophysical logs, dynamicformation testers, production logging, and pressure-transient testing. With theadvent of permanent sensing technologies and the development of methods ofproduction-data inversion or history matching, a new form of cased-holediagnosis can be envisaged, with improved spatial and temporal coverage andwithout the need for in-well intervention and interruption of production. Theimpact of such methods on reservoir-scale characterization can also besignificant.
There are two main preconditions for the development of such a methodology,one concerning sensing technology and the other concerning interpretationmethodology. Permanent sensing technology has made great progress during thelast decade, with the development of single-point and distributed measurementsthat can be deployed with the completion (pressure, flow rate, and distributedtemperature). However, these systems are typically developed as standalonemeasurement units and do not enjoy the required degree of integration. Currentmodeling methods, however, can be used to provide an incentive for suchintegration.
The well-diagnosis problem is decoupled in our investigation into diagnosisof flow condition in the wellbore and diagnosis of near-wellbore formationcharacteristics. (By "near-wellbore," we mean the wellbore gridblock scale.)This is partly to adhere to the conventional demarcation between productionlogging and dynamic formation evaluation and partly to show the naturalconsequence of the mathematical problem. Basically, the wellbore-diagnosisproblem (determination of flux distribution, as in production logging) cantreat the formation simply as a boundary condition, but theformation-evaluation problem cannot do the same (i.e., treat the wellboreinterface as a boundary condition) because evaluation is based on measurementsmade inside the wellbore. Thus, both the wellbore and the formation have to betaken into account. (Sensors that are in direct contact with the formation, asmentioned in the Summary, are emerging.8 Therefore, the evolution of thisproblem is to be expected.) In this study, the permanent or in-situ analog ofdynamic formation evaluation is investigated. The in-situ analog of productionlogging is investigated in a parallel study.
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