Geophysical imaging of the Luhoi geothermal field, Tanzania

The Luhoi prospect is a coastal basin located within Rufiji Trough along the passive continental margin of western Indian Ocean of Tanzania, a sector extending south of the termination of the eastern branch of the African Rift System. The structural pattern is dominated by tectonic features belonging to the WNW-ESE Tagalala Trend and to the NE-SW Selous Trend that have been active until recent times. The thermal manifestations are mostly located along a WNW-ESE direction flowingfollowing the Ruhoi River, in the south-western sector of the focal study area. The Wingoyongo Hill, located in the north-eastern sector of the focal area, forms a morphological high where emissions of H2S and bituminous staining were observed. Here, an old well intersected 800 m of quartz sandstone with minor intercalations of siltstone and claystone (Kipatimu Series, Lower Cretaceous). Magnetotelluric (MT), time-domain electromagnetic (TDEM) and gravimetric geophysical surveys were carried as part of a geoscientific study funded by the Ministry of Foreign Affairs of Iceland through Icelandic International Development Agency (ICEIDA) and the Nordic Development Fund (NDF). The goal of the survey was to advance the state of knowledge of the Luhoi geothermal prospect, in order to elaborate the conceptual model of the field. The survey area extends over a surface of approximately 75 km2, designed to include the Luhoi hot springs and the Wingoyongo fumaroles. The gravimetric data set is composed of 124 measurements collected on a regular grid at a nominal spatial sampling of 800 m, and 16 more to infer the regional field. The residual Bouguer anomaly map shows an elongated gravimetric high trending NE-SW with values up to 3 mGal, surrounded by gravimetric lows up to -2 mGal. Forward and inverse 2D/3D models image an asymmetrical horst like structure trending NE-SW. Both the thermal manifestations and the Wingoyongo Hill are aligned along the NW flank of the horst. Since the Wingoyongo well intersected sandstones for about 800 m, the horst like structure is interpreted as made by the Kipatimu sandstones. The two depressions bordering the horst like structure are filled with lower density materials, likely siltstones, claystones and/or mudstones, with an estimated maximum thickness of 1.1 km. The MT and TDEM data were acquired at 76 locations, with a nominal spatial sampling of 750 m. The static shift effect has been corrected by TDEM/MT phases joint inversion. MT impedances and tippers have been estimated by means of the remote reference technique with robust processing methods coupled with a coherence rejection scheme. Resistivity 3D inversion reveals two conductive anomalies coincident with the low-density sedimentary rocks bordering the horst structure. A clear updoming of resistivity marks the NW flank of the horst and it is interpreted as due to a combined effect of different alteration, lithology and fluid content and to reflect the main upflow of the geothermal system

Three-dimensional geophysical modelling of Kiejo-Mbaka geothermal field, Tanzania

The Kiejo-Mbaka geothermal field is located close to the eastern margin of the Karonga Rift Basin and is part of the Rungwe volcanic province where the EARS splits up into its Western and Eastern branches in southern Tanzania. The area is characterised by a Precambrian gneiss metamorphic basement complex, outcropping along the NW-trending, SW-dipping Mbaka fault. Geothermal manifestations mainly consist of hot springs, flowing close to the Mbaka fault. An integrated geophysical survey was carried out over the Kiejo-Mbaka geothermal field by TGDC (Tanzania Geothermal Development Company), under the supervision of ELC-Electroconsult (Italy). The campaign included 76 Magnetotelluric (MT) and Transient Electromagnetic (TEM) soundings and 133 gravity measurements; a dense station grid allowed for a detailed geophysical 2D and 3D modelling. Two and 3D gravity modelling indicate that the positive residual Bouguer anomaly can be explained by a high density (3 g/cm3) body, constituting the gneiss basement, elongating NW-SE. NE and SW of it, lower density layers (2.5 g/cm3) are observable; the attitude of their bottoms is compatible with the Mbaka fault direction and the Livingstone fault trend (NNW). We found that 3D MT inversion was the only tool giving a reliable resistivity imaging in the Mbaka prospect. From the final 3D MT model, a very resistive body (>2000 Ohm m) deepening toward SE is visible; this body represent the gneiss basement, and the surfaces delimiting it are associated with the Mbaka fault and the Livingstone fault trend. Three conductive zones (less than 10 Ohm m) have been identified: two of them affect the Mbaka fault footwall, NE of the resistive basement, while another one is located beneath the plain, SE of it. This latter zone shows a thickness of about 1 km. It is apparent that the low-density regions well correspond with the high-conductivity zones imaged by the MT 3D inversion. The integrated geophysical interpretation then leads to two possible geological scenarios: these regions can be constituted by (post-rift) sediments (possibly affected by low-T geothermal alteration) or by intensively fractured and low-T altered basement; however, we stress that the possible geothermal alteration is not necessarily related to the present-day geothermal activity, and caution should be taken in result interpretation

Focused Inversion of Gravimetric and Magnetotelluric Data for Geothermal Investigations

Focused inversion techniques may be applied to geophysical data inversion in order to image complex structures in the subsoil. These algorithms may image complex \u201cblocky\u201d structures giving useful information in geothermal exploration that may be smoothed out by standard inversion algorithms that use stabilizer that penalize sharp transitions. We have tested the modified total variation and the maximum gradient support stabilizers in the inversion of synthetic and field magnetotelluric and gravimetric data. The gravimetric data from the Luhoi geothermal prospect have been used to map the sharp density transition between the sandstone and the overlying claystone layers. The resulting horst structure imaged in 2D and 3D models by the maximum gradient support stabilizer solution allow to trace the main fault system that drives the up-flow of hydrothermal waters. The 1D magnetotelluric \u201cblocky\u201d models with lateral constrain (pseudo-3D) image the lithological contact between the claystone and sandstone far from the horst area and reveal resistivity variations in the claystone layer associated with sand lenses. In the horst area, resistivity models image hydrothermal alteration affecting the sandstone layer

Geophysical Exploration of the Kiejo-Mbaka Geothermal Field, Tanzania

The Kiejo-Mbaka geothermal prospect (Tanzania) lies along the eastern margin of the late Miocene - Pliocenic Karonga Rift Basin, and is part of the Rungwe volcanic province. The prospect is characterised by an uplifted and outcropping block of Precambrian Gneiss basement, limited toward SW by the NW-trending, SW-dipping Mbaka Fault. The geothermal manifestations mainly consist of hot springs, occurring along this fault. To get a detailed assessment of the prospect, an integrated geophysical survey has been carried out by TGDC (Tanzania Geothermal Development Company), with the supervision of ELC-Electroconsult (Italy). A dense station grid was adopted, comprising 76 Magnetotelluric (MT) and Transient Electromagnetic (TEM) soundings and 133 gravity measurements. The 2/3D gravity modelling depicted the structure of the basement, primarily consistent with a tilted and uplifted block of the Karonga half-graben. The high-density basement block (3000 kg/m3) is surrounded by lower density layers (2500 kg/m3), lying beneath the plain SW of the Mbaka fault and NE of it. Magnetotelluric dimensional analysis indicated strong 3D conditions and yx-component phases often beyond 90\ub0. The MT 3D modelling identified a resistive body (>2000 Ohm m) deepening toward SE and representing the gneiss basement. Two conductive layers (<10 Ohm m) are located on the ridge NE of the Mbaka fault, and another one (<5 Ohm m) lies beneath the plain, showing a thickness of about 1 km. We found a strict correlation between the low-density and the high-conductivity layers. This leads to hypothesise the presence of syn/post-rift sediments possibly hosting a geothermal reservoir

Magnetic, gravimetric, TDEM and magnetotelluric joint interpretation at the Luhoi geothermal field, Tanzania

We show the interpretation of the gravimetric, magnetic, TDEM and magnetotelluric geophysical campaign carried out to better constrain the geothermal conceptual model of the Luhoi geothermal field in Tanzania. Geophysical modelling has imaged a NE trending horst 1 km wide and 5 km long formed by the denser Kipatimu (Lower Cretaceous) sandstones surrounded by the Upper Cretaceous Ruaruke claystones down-thrown up to 1 km by normal faulting. Ruaruke claystones show low resistivity (1-10 Ohm m) primarily due to its clay content, while the Kipatimu sandstones have generally higher resistivity (10-30 Ohm m) because of their prevalent electrolytic conduction

Focused Geophysical Imaging of the Chiweta Geothermal Field (Malawi)

Geophysical surveys may image buried tectonic structures and variations of lithology, hydrothermal alteration and porosity/fluid content of geothermal fields and inverse models can be directly used for the assessment of the conceptual models. However, conventional interpretation is commonly based on minimum-structure inverse modelling that produces inherently smooth and blurred images of the investigated geological structures (e.g Zhdanov, 2002). Therefore, while smooth modelling helps inversion convergence and prevent artefacts in the solutions, some important features with sharp transitions can be missed or smoothed out. Typical examples are the lithological variations between the sedimentary infill and the bedrock in a basin or the bedrock steps due to faulting in graben/horst structures. Focused geophysical imaging (Portniaguine and Zhdanov, 1999) with different regularization methods can be more effective to detect sharp boundaries because they did not excessively penalize sharp physical property variations. The total modified variation (MTV, Acar and Vogel, 1994) and the minimum gradient support (MGS, Portniaguine and Zhdanov, 1999) stabilizers were applied to the inversion of gravimetric and magnetotelluric data collected at the Chiweta geothermal prospect in Malawi. The gravimetric data was used to map the interface between the Karoo formation and the underlying Precambrian gneiss basement complex, assuming a density contrast of 200 kg/m3. The resulting horst-graben structure imaged by the 2D and 3D MTV and MGS inversion allowed to identify major faults affecting the basement and possibly driving the up-flow of hydrothermal fluids. The 1D magnetotelluric MTV and MGS inversions with lateral constrain provided a focused pseudo-2D image of the resistivity distribution. The models showed the lithological contact between the Karoo formation and the basement complex in the central portion of the survey area. Geothermal alteration in the Karoo formation has been revealed by different conductive anomalies. Some of them are associated with low temperature clay alteration in the Chiweta hot springs area, while others may represent fossil geothermal zones. Good correspondence between higher density and resistivity values has been observed where geothermal alteration is plausibly weaker or absent. It was found that focused inversion is strongly dependent upon the initial model and the chosen inversion parameters, but if a proper choice is done, it can be an effective tool to get detailed geological images. It was concluded that it can be considered as a refinement of the classical maximum smoothness approach, to be used when abrupt physical property changes are expected. REFERENCES Acar, R., and Vogel, C. R. \u201cAnalysis of total variation penalty methods\u201d Inverse Problems, 10, 1217-1 229 (1994). Portniaguine, O., and Zhdanov, M. S. \u201cFocusing geophysical inversion images\u201d. Geophysics, 64, 3, 874-887 (1999). Zhdanov, M. S. \u201cGeophysical inverse theory and regularization problems\u201d, Methods in Geochemistry and Geophysics, 36, Elsevier (2002)

Smooth MT Transfer Function Estimation by an Inverse Scheme

The geophysical exploration of geothermal areas strongly relies upon Magnetotellurics (MT) method, that exploits the measurement of the low-power natural EM field at the Earth's surface. Through the estimation of the MT transfer functions (TF), relating the electric to the magnetic field, the subsurface resistivity distribution can be inferred. Due to the diffusive nature of the low-frequency EM field, the MT TF's are inherently smooth, and smoothness is the main criterion adopted by EM community to assess the estimation quality. In the presence of Gaussian noise, the frequency-domain the least squares (LSQ) method provides the best possible estimate; natural MT data, however, contains a significant amount of non-stationary data that constitute outliers for the LSQ procedure. These outliers make the TF\u2019s sharp at several frequencies, according to the nature of the noise. In order to circumvent this problem, robust methods were introduced, and provide a smooth TF, if non-stationarity is a minor fraction of the record. However, as geothermal development proceeds on a global scale, investigations can involve densely populated and industrialised areas. In these zones, high-power artificial is more likely present. Since these disturbance signals can by persistent, robust methods can fail; moreover, preliminary filtering can be ineffective. In these conditions, the applicability of MT is severely hampered. In some cases, smoothness is a-posteriori introduced by splines or smoothing procedures, but this approach lacks physical consistency. It can also be part of estimation methods but implying the adoption of some arbitrary assumptions. Here we propose a new heuristic algorithm to reach the maximum TF's smoothness through an inverse scheme applied to event rejection in frequencydomain. The algorithm searches for frequency-dependent power thresholds to be applied to the events, in order to achieve the maximum smoothness in the TF's. The smoothness is the objective function to be minimized, and the model space is constituted by the infinite set of threshold vectors. We found that after the completion of the process, the distribution of the event powers is more Gaussian, and then, more suitable for LSQ estimation; the corresponding residuals are consequently closer to a Rayleigh distribution. Physical consistency of the resulting TF has been tested by 1D inversion. The algorithm can, therefore, be combined with the MT remote-reference technique, and we found that it is effective to reduce the effects of artificial strong-power signal that can deteriorate the acquisitions. We present the successful application of this new technique to MT data collected over an East African Rift System geothermal area