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In Nigeria it is a statutory requirement to frequently perform multi-rate test (MRT) on gas wells to update well deliverability and for optimal reservoir management. Analysis of MRT test data provides information on well potential, average reservoir pressure, flow correction, skin factors, condensate and water rate. This information is useful when calibrating well models and in reservoir management. Allthisinformation when not properly estimated can have a huge impact in reserve estimation as well as production forecasting. Traditionally, MRT testing is done using a mobile tester. The inability to conduct MRT tests frequently using themobile tester is due to budget constraints and associated deferment or flaring affectingobligation to meet gas sale agreement. Other demerits associated with the traditional approach to MRT include large personnel exposure, mobilization of heavy equipment, high environmental footprint, inability to flow well to potential due to flare limitation and difficulty in reconciling test rates with actual rates. Due to these limitations, an alternative testing method is proposed. The proposed approach makes frequent MRT's possible and attractive from both economic and HSSE standpoint. The proposed method discussesusing existing gas central processing facility to conduct MRT. This new method offers a major advantage over the former since it requires little or no equipment mobilization, no flaring nor deferment, reduced number of personnel exposure, no test rate limitation nor rate reconciliation, all of which can be achieved at a significantly lower cost, reduced HSSE exposure and testing duration. Pilot tests were successfully carried out on well X, well Y & well Z. In each case there were zero incidents, zero deferment and zero production loss. This method saved $2.34M and gained some volume of gas which would have been lost to flaring if testing was done using the traditionalmobile tester. These three pilot examples demonstrate that MRT's can be performed more frequently using an existing gas central processing facility provided all of the metering equipment are installed and that the activities is meticulously planned to capture all of the required data.
In Nigeria it is a statutory requirement to frequently perform multi-rate test (MRT) on gas wells to update well deliverability and for optimal reservoir management. Analysis of MRT test data provides information on well potential, average reservoir pressure, flow correction, skin factors, condensate and water rate. This information is useful when calibrating well models and in reservoir management. Allthisinformation when not properly estimated can have a huge impact in reserve estimation as well as production forecasting. Traditionally, MRT testing is done using a mobile tester. The inability to conduct MRT tests frequently using themobile tester is due to budget constraints and associated deferment or flaring affectingobligation to meet gas sale agreement. Other demerits associated with the traditional approach to MRT include large personnel exposure, mobilization of heavy equipment, high environmental footprint, inability to flow well to potential due to flare limitation and difficulty in reconciling test rates with actual rates. Due to these limitations, an alternative testing method is proposed. The proposed approach makes frequent MRT's possible and attractive from both economic and HSSE standpoint. The proposed method discussesusing existing gas central processing facility to conduct MRT. This new method offers a major advantage over the former since it requires little or no equipment mobilization, no flaring nor deferment, reduced number of personnel exposure, no test rate limitation nor rate reconciliation, all of which can be achieved at a significantly lower cost, reduced HSSE exposure and testing duration. Pilot tests were successfully carried out on well X, well Y & well Z. In each case there were zero incidents, zero deferment and zero production loss. This method saved $2.34M and gained some volume of gas which would have been lost to flaring if testing was done using the traditionalmobile tester. These three pilot examples demonstrate that MRT's can be performed more frequently using an existing gas central processing facility provided all of the metering equipment are installed and that the activities is meticulously planned to capture all of the required data.
Given sufficient performance and other data, material balance (MB) is a common method of determining the hydrocarbons initially in-place (HCIIP) in a reservoir. The application of this method requires, as a minimum, historic cumulative production (including injection) and average reservoir pressure. However, determination of historic average reservoir pressures would require shut-in of wells, hence production deferments. As an improvement to the classical MB, the dynamic material balance (DMB) method was developed by Mattar and Anderson (2005). Unlike the MB method, direct measurements of average reservoir pressure are not critical to DMB. In its basic form, the implementation of DMB requires historic production rates, flowing bottomhole pressures and cumulative production, thereby eliminating associated deferments. Although DMB has performed satisfactorily in some applications, its overall robustness remains to be fully explored. This paper conducts rigorous sensitivity checks on selected DMB models. Based on insights gained, their relative strengths and weaknesses are highlighted. To keep the problem tractable, detailed simulations are performed on different three-dimensional (3D) multiphase homogenous reservoir models of known HCIIP. Different cases are simulated, generating relevant performance datasets to evaluate DMB. The parametric tests conducted on this undersaturated compressible oil reservoir include (i) constant vs. variable production rates; (ii) rate hysteresis; (iii) vertical vs. horizontal well; (iv) single vs. multiple wells; (v) healthy vs. damaged well; and (vi) variable skin factors, with hysteresis. Within the parameter space examined, simulation results show that DMB performance (e.g. HCIIP) is sensitive to some of the parameters and subsurface realisations investigated. Against this background, some improvements and guidelines are proposed to enhance the capability and performance of DMB as a technique for reservoir surveillance.
This study analyzes recently released proprietary daily production data from 31 decommissioned dry gas fields located on the UK Continental Shelf (UKCS). First, the hydrocarbon fields in the UKCS region were assigned to five groups, based on their geological source origin. The data analyzed here are from two lease areas comprising gas fields, sourcing from two of the five groups distinguished. One set of wells produced from Carboniferous Westphalian sandstones, the other from Permian Rotliegendes sandstones: both reservoir types remain active sub-salt targets. The production profiles of the 31+ legacy wells analyzed were grouped into four types: (1) Wells part of multi-well clusters producing from large fields, with production output controlled by facility access allocation; (2) Problem wells, with poor production and long downtime; (3) Wells with frequent shut-in days but excellent recovery; and (4) Fast clean producers; single well production profiles showing continuous decline without major interruptions, other than slight adjustments of choke settings. Two Permian gas fields (Mimas and Tethys) and one Carboniferous gas field (Kelvin) were produced with fast and clean producer wells. These wells appeared also equipped with bottomhole gauges which together with choke-settings and wellhead pressures, gives a comprehensive record of historic well performance. The historic well performance was analyzed using various bootstrapped data sets (6, 12- and 18-months production), which were least-mean-square-error (LMSE)-fitted with a traditional Arps decline curve analysis (DCA) method. The EUR forecast based on the bootstrapped Arps DCA (6, 12, 18 months) was compared with the known actual EUR based on the full historic well performance record. Based on our evaluation, a fast LSME fit of Arps DCA on early bootstrapped well data for 18 months appeared to give reliable estimates for the actual long-term EUR/well for two fields (Kelvin and Tethys). However, a third field (Mimas) required 5 years of bootstrapped data to achieve reliable EUR estimates.
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