This paper presents a gravity inversion method for determining the volumes of bodies with pre-established density contrasts. The method works step-by-step on a prismatic partition of the subsurface volume, expanding the anomalous bodies to fit the observed gravity values in a systematic exploration of model possibilities. The process is treated in a 3-D context; at the same time, it can determine a simple regional trend. Moreover, positive and negative density contrasts are simultaneously accepted. The solution is obtained by a double condition: (1) the 2 -fitness to the observed gravity data (model fitness) and (2) the minimization of the total (weighted) anomalous mass (model smoothness). A positive parameter is used to balance the two minimization terms. The method is applied to a simulated example and also to a real example: the volcanic island of Gran Canaria (Canary Islands, Spain). In both cases, the results obtained show the possibilities of the method.

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The use of genetic algorithms in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the non-linearity inherent in such applications. We have implemented a genetic algorithm to efficiently invert a set of gravity data. Employing several fixed density contrasts, this algorithm determines the geometry of the sources of the anomaly gravity field in a 3-D context. The genetic algorithms, based on Darwin's theory of evolution, seek the optimum solution from an initial population of models, working with a set of parameters by means of modifications in successive iterations or generations. This searching method traditionally consists of three operators (selection, crossover and mutation) acting on each generation, but we have added a further one, which smoothes the obtained models. In this way, we have designed an efficient inversion gravity method, confirmed by both a synthetic example and a real data set from the island of Fuerteventura. In the latter case, we identify crustal structures related to the origin and evolution of the island. The results show a clear correlation between the sources of gravity field in the model and the three volcanic complexes recognized in Fuerteventura by other geological studies.

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Abstract. Gravimetric studies are becoming more and more widely acknowledged as a useful tool for studying and modeling the distributions of subsurface masses that are associated with volcanic activity. In this paper, new gravimetric data for the volcanic island of S•o Miguel (Azores) were analyzed and imerpreted by a stabilized linear inversion methodology. An inversion model of higher resolution was calculated for the Caldera of Furnas, which has a larger density of data. In order to filter out the noncorrelatable anomalies, least squares prediction was used, resulting in a correlated gravimetric signal model with an accuracy of the order of 0.9 mGal. The gravimetric inversion technique is based on the adjustmere of a three-dimensional (3-D) model of cubes of unknown density that represems the island's subsurface. The problem of non-uniqueness is solved by minimization with appropriate covariance matrices of the data (resulting from the least squares prediction) and of the unknowns. We also propose a criterion for choosing a balance between the data fit (which in this case corresponds to residues with rms of the order of 0.6 mGal) and the smoothness of the solution. The global model of the island includes a low-density zone in a WNW-ESE direction and a depth of the order of 20 km, associated with the Terceira rift spreading center. The minimums located at a depth of 4 km may be associated with shallow magmatic chambers beneath the main volcanoes of the island. The main high-density area is related to the Nordeste basaltic shield. With regard to the Caldera Furnas, in addition to the minimum that can be associated with a magmatic chamber, there are other shallow minimums that correspond to eruptive processes.

Summary The application of a gravity inversion method enables us to obtain a 3‐D density contrast model of the upper crustal anomalies of the volcanic island of Lanzarote (Canary Islands). For this, we use a network of 296 gravity stations distributed over the whole island, and a digital terrain model of about 45 000 terrestrial and oceanic data to determine the corresponding terrain correction. A density value of 2480 kg m−3 is chosen for this correction by means of a new approach. The resulting Bouguer anomaly is analysed by means of a least‐squares prediction which gives us a mean level of uncorrelated observational noise of about 1.2 mgal. This anomaly is considered in order to obtain independent information about the inner anomalous mass density distribution by means of a 3‐D gravity inversion based on a systematic exploration on a prismatic partition of the subsoil volume, and adopting a priori values of the density contrast (positive and negative) to determine the geometry of the anomalous bodies. The problem of non‐uniqueness of the solution is avoided by using a minimization mix condition on the weighted residuals and the weighted whole anomalous mass. The structural solution is finally presented by means of horizontal sections and vertical profiles. A main intrusive body is located under the central‐eastern area and could correspond to a dilated volcanic activity of shield formation. It shows a prismatic form of more than 15 km depth, subducted with only the ridges remaining as horst blocks. Moreover, the SW and NE extreme areas of the island show smaller and shallower positive bodies, interpreted as less‐developed magmatic intrusions. Conversely, several density lows offer interesting shallow alignments, 45°N (ENE–WSW) and 125°N (WNW–ESE), which could be associated with a fracture system corresponding to structural stress, and also correlate with historic eruptions, such as, for instance, the Timanfaya eruption. The monitoring of several geophysical parameters at two underground geodynamic stations, in the NE zone of the island and Timanfaya, shows characteristic differences between the two zones which confirm crustal anomalies in the second station.

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