Geophysical monitoring techniques offer the only noninvasive approach capable of assessing both the spatial and temporal dynamics of subsurface fluid processes. Increasingly, permanent sensor arrays in boreholes and on the ocean floor are being deployed to improve the repeatability and increase the temporal sampling of monitoring surveys. Because permanent arrays require a large up-front capital investment and are difficult (or impossible) to re-configure once installed, a premium is placed on selecting a geometry capable of imaging the desired target at minimum cost. We present a simple approach to optimizing downhole sensor configurations for monitoring experiments making 1 use of differential seismic traveltimes. In our case, we use a design quality metric based on the accuracy of tomographic reconstructions for a suite of imaging targets. By not requiring an explicit singular value decomposition of the forward operator, evaluation of this objective function scales to problems with a large number of unknowns. We also restrict the design problem by recasting the array geometry into a low dimensional form more suitable for optimization at a reasonable computational cost. We test two search algorithms on the design problem: the Nelder-Mead downhill simplex method and the Multilevel Coordinate Search algorithm. The algorithm is tested for four crosswell acquisition scenarios relevant to continuous seismic monitoring, a two parameter array optimization, several scenarios involving four parameter length/offset optimizations, and a comparison of optimal multi-source designs. In the last case, we also examine trade-offs between source sparsity and the quality of tomographic reconstructions. One general observation is that asymmetric array lengths improve localized image quality in crosswell experiments with a small number of sources and a large number of receivers. Preliminary results also suggest that highquality differential images can be generated using only a small number of optimally positioned sources.2