The Well Testing Program at the Heber Geothermal Field

1985 ◽  
Author(s):  
W.J. Da Sie ◽  
V.T. Hoang
2021 ◽  
Author(s):  
Mitsuo Matsumoto

This chapter describes an approach to estimate reservoir productivity during the active exploration and development of a geothermal prospect. This approach allows a reservoir model to be updated by overcoming the severe time limitations associated with accessing sites for drilling and well testing under snowy and mountainous conditions. Performed in parallel with the conventional standard approach, the new approach enables us to obtain a first estimate of the reservoir productivity at an early time and to make successful project management decisions. Assuming a practical geothermal field, the procedures of the new approach are demonstrated here in detail. Finally, frequency distributions for the expected production rates and changes in the reservoir pressure at an arbitrary time are obtained during an assumed operational period.


2021 ◽  
Author(s):  
Adhi Naharindra ◽  
Mohd Hisham Abd Hamid ◽  
A Ghafar A Halim ◽  
Sarah M Affandi ◽  
W M W Ibrahim ◽  
...  

Abstract This paper demonstrate a unique combination of techniques and equipment that enabled dynamic reservoir evaluation process using simplified Drill Stem Test (DST) string and completion accessories. The well testing was conducted on a shallow slanted offshore well, drilled into faulted reservoirs with multilayer and complex fluids environment. Key technical challenges to perform well testing includes designing a custom DST string to cater for the multilayer reservoir and articulating a surface well testing equipment that capable of efficient separation to ensure safe and environmental friendly disposal while having accurate flowrate measurements, to deliver good interpretable data given that the uncertainty and complexity of the formation and the well itself. During drilling campaign, contingency plan to mitigate against losses was implemented which had a significant impact on the well testing program. As such, uncertainty-based well test design and interpretation methodology was used to address this and to achieve well objectives. This involved numerical model analysis considering reservoir uncertainties and their interaction with each other, to identify which parameters can be interpret confidently and to indicate the test duration for the well testing program. Since the area is nearby to producing fields, several cases model based on reservoir pressure regime was also constructed during the design stage to tolerate flexibilities for the decision tree. The well testing was successfully conducted result from integrated approach to well test design and realtime data support throughout the operation along with innovative DST string design, customize completion accessories for multiple zones testing and adaptive intervention tools for highly deviated well. Matching with nearby wells were also conducted during monitoring to predict future pressure behaviour which allow for the duration of final build-up to be optimized. Given that Health, Safety and Environment (HSE) is the top of priority, an important aspect of the surface well testing package was the water treatment equipment to treat the produced water from reservoir before being discharge in order to guarantee safe environmental disposal. The well was successfully test at maximum flowrate 2,000bpd of oil and 20MMscf/d of gas with traces of produced water. Data gathered thru the Tubing Stem Test (TST) can used to interpret reservoir parameters and all the well testing objectives were successfully achieved despite the many challenges encountered during the drilling campaign and design stage. The end results may contradict traditional testing methods for pressure transient analysis, but hopefully this paper might create the opportunity to replicate TST as quick and effective reservoir evaluation in other parts of the world.


Author(s):  
Solomon Kahiga ◽  
Nicholas Mariita ◽  
Njenga Mburu

Ground subsidence studies have been done on Olkaria geothermal field conventionally by comparing levels on benchmarks over years. Interferometric synthetic aperture radar (InSAR) systems have also been used to map surface deformation of small spatial extent. For the prediction of future dynamics of land subsidence in Olkaria due to geothermal resource exploitation, a hydrogeological conceptual model has been developed. In this model, hydrologic geothermal fluid properties are analysed and a relationship between the reservoir and geology of the wells established, subsidence is computed numerically. The model takes into account the hydrogeological condition of Olkaria geothermal field. Hydrological reservoir parameters are computed from well testing data. The study considers the Injectivity indices of the various wells under study as pre-computational indicator of the expected subsidence extents. Both two- and three-dimensional geological cross-sections are modelled with the rockworks software by inputting stratigraphic data for Olkaria domes. Geological simulations are used to study subsidence by assigning the ground formation with virtual material that deformed according to some essential relations in Rockworks computer software. Production zones are determined by a comparison between the well properties and corresponding well geology. Subsidence is then computed by the Tezarghi’s modified equation. Cumulative subsidence figures from the computation are in the range of 0.095-0.537m, without any reinjection. Computed values are then mapped in ArcGIS to develop a representative subsidence map. By application of these modelling and numerical computation methods, ground subsidence was effectively predicted using the five selected wells in Olkaria domes field. The hydrogeological model developed, and mapping is an important tool in the planning and development of a reinjection schedule and in subsidence mitigation. Subsidence prediction also is important in design of infrastructure which will be strong enough to resist the forces caused by subsidence.


1980 ◽  
Vol 20 (06) ◽  
pp. 555-566 ◽  
Author(s):  
Constance W. Miller

Abstract The early-time response in the well testing of a homogeneous reservoir customarily is expected to give a unit slope when the logarithm of pressure is plotted vs. the logarithm of time. It is shown that this response is a special case and that another nondimensional parameter must be defined to describe the set of curves that could take place for each value of the wellbore storage coefficient C . In addition, the effect of temperature changes along the bore is shown to increase the time when wellbore storage is important. Introduction The petroleum industry's technique of assessing oil and gas reservoirs by well testing has been extended to the geothermal field by a number of workers. However, at least two important differences between a geothermal field and an oil or gas field must be considered in analyzing geothermal well test data. First the kh/mu value of a geothermal field is usually much larger than that of an oil or gas field because the reservoir thickness h is greater in a geothermal field and the viscosity mu is smaller (k is the permeability). Second, heat loss in the wellbore, which can be ignored in oil and gas fields, is significant in geothermal bores.The concept of wellbore storage - which has been considered quite extensively and refined in such detailed studies as those of Agarwal et al., Wattenberger and Ramey, and Ramey - usually is treated as a boundary condition on the reservoir flow. The boundary condition used is (1) where dp w/dt is the flowing pressure change with time in the wellbore. However, dp w/dt is not necessarily independent of position in the well. When dp w/dt is dependent on the measurement point, a plot of log (p sf) vs. log (t) will not result in a unit slope at early times. This study will consider wellbore storage by looking at the flow in the well itself while treating the reservoir as simple homogeneous radial flow into the well.Heat loss from the well and temperature changes along the bore also have been ignored because oil and gas news can be treated as isothermal. Heat transfer from the well and heating of the fluid in the well is usually a very slow process. When very long times are considered, these temperature effects can become important. Once the early transient behavior is over and a semilog straight line of p sf vs. log(t) is expected in the pseudosteady region, temperature changes in the well can alter the slope of that line so that the slope would no longer be q mu/4 pi kh. The duration and importance of any temperature changes will be considered.A numerical model of transient two-phase flow in the wellbore with heat and mass transfer has been developed. It is used to investigate (1) the early-time interaction of the well flow with that of the reservoir and (2) the longer-time effect of temperature changes on the well test data. Concept of Wellbore Storage Wellbore storage is the capacity of the well to absorb or supply any part of a mass flow rate change out of a well/reservoir system. For a change in flow rate at the surface of the well, the sandface mass flow rate usually is expressed as (2) SPEJ P. 555^


Author(s):  
Solomon Namaswa ◽  
John Githiri ◽  
Nicholas Mariita ◽  
Maurice K’Orowe ◽  
Nicholas Njiru

Geophysical methods including seismology, resistivity, gravity, magnetic and electromagnetic have been put in use for geothermal resource mapping at the Great Olkaria Geothermal field for decades. Reservoir temperature distribution and the electrical conductivity of rocks mainly depend on the same parameters such permeability, porosity, fluid salinity and temperature. This research focused on the integration of Olkaria Domes geothermal well testing temperature and geophysical Electromagnetic resistivity data with the aim of establishing an alternative estimation method for temperature of the reservoir through machine learning Analytics. To achieve this, Data-Driven Discovery Predictive Model Algorithm was built using Python programming language on Anaconda framework. The open-source web based application Jupyter Notebook for coding and visualization was used. Decision Tree Regression, Adaptive Booster Regression, Support Vector Regression and Random Forest Regression were used. The model performance was evaluated using R-Score and Mean Absolute Error metrics. Based on these performance score, the best performing model was suggested to predict subsurface temperature from resistivity. Training the model using the DTR algorithm approach provides superior outputs with R2 of 0.81 and lowest MAE of 29.8. The DTR algorithm could be implemented in determination of subsurface Temperature from resistivity in high temperature hydrothermal fields.


1979 ◽  
Author(s):  
Jesus Rivera-R. ◽  
Mehmet Saltuklaroglu

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